Whatsnew(RMark)
Whatsnew()所属R语言包：RMark
Summary of changes by version
版本的变更摘要
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A good place to look for changes. Often I'll add changes here but don't always get to it in the documentation for awhile. They are ordered from newest to oldest.
寻找改变的好地方。我常常会添加改变，但并不总是得到它的文档中一段时间。他们下令从新到旧。
Details
详细信息----------Details----------
Version 2.0.9 (1 Dec 2011)
版本2.0.9（2011年12月1日）
Patch was made to make.mark.model to fix bug in PIM creation for a multi-session model and there was just 1 session. Thanks to Erin Roche for helping to identify
补丁make.mark.model修正错误在PIM创造的一个多会话模式和有仅有1届。感谢艾琳罗氏帮助确定
Patch was made to make.mark.model to fix bug in handling of mlogits for pi and Omega parameters with more than one group. These parameters were introduced with the RDMSMisClass and other new models that were recently
补丁make.mark.model修正错误的mlogits处理PI欧米茄参数的一组以上的。这些参数的的RDMSMisClass等新车型最近推出
Additional changes were made to export.MARK to re-fix changes for robust
更多的变化export.MARK重新修复为强大的
A function mark.wrapper.parallel written by Eldar Rakhimberdiev provides a parallel processing version of mark.wrapper. See the example in the help for the function. The parallel version is functionally the same and can be used in place of mark.wrapper to run sequentially or in parallel. It does not include the run
函数mark.wrapper.parallel写的埃尔达尔穆Rakhimberdiev提供的并行处理版本的mark.wrapper中。请参见示例中的帮助功能。并行版本在功能上是相同的，可以被用来代替mark.wrapper顺序或并行地运行。它不包括运行
A bug was fixed in get.real which caused an R error for a triangular PIM that had only a single entry. Thanks to Amanda Goldberg for discovering and reporting this error.
修正了在get.real一个三角形的PIM，只有一个条目的错误造成的R。感谢阿曼达戈德堡发现并报告了这个错误。
Version 2.0.8 (7 Oct 2011)
版本2.0.8（2011年10月7日）
Both setup.model and setup.parameters were re-written to use data files models.txt and parameters.txt to define models and parameters which should make it easier to add new models. The latter function is now much simpler and
这两个setup.model和setup.parameters被重新编写以使用数据的文件models.txt和parameters.txt定义的模型和参数，应该可以更容易地添加新的模式。后者的功能是现在要简单得多，
Model RDOccupEG now allows sharing Epsilon and Gamma parameters. Epsilon is the dominant parameter which gets the share=TRUE argument. See RDOccupancy for an example. Thanks to Jake
，型号RDOccupEG现在允许共享的ε和伽玛参数。 Epsilon是最重要的参数，它得到的份额= TRUE参数。见RDOccupancy一个例子。由于杰克
To avoid confusion, the arguments component and component.name were removed from the parameter specification because these have not been required since v1.3 when full support for individual covariates were included. Likewise the argument covariates in mark and make.mark.model was removed because it was only needed to support the
为了避免混淆，参数component和component.name从参数规格，因为这些都没有必要的，因为v1.3的全力支持为个人的变量。同样的说法covariatesmark和make.mark.model被删除，因为它是只需要支持
export.MARK was modified so that if all individual covariates are output,
export.MARK被修改，如果所有个体变项为输出，
Many more models were added to those supported in RMark. Now 92 of the 137 models in MARK are supported. See MarkModels.pdf in the RMark directory of your R library to see which models are supported (in red). Most of the remaining unsupported models are versions with mis-identification error and
还有更多的车型添加到支持RMark的。现在的137车型在MARK 92的支持。见的RMark R库的目录，看看哪些机型都支持（红色）MarkModels.pdf在。大部分的剩余的不支持的模型版本与误识别错误和
Previously RMark stored the input file in a temporary file Markxxx.tmp. Using a common filename caused problems when more than one model were spawned to different CPUs, so now it uses a random temporary file name. It also no longer uses common file markxxx.vcv. Thanks to Glenn
在此之前，RMark存储在一个临时文件Markxxx.tmp的输入文件。使用常见的文件引起的问题时，多个模型产生不同的CPU，所以现在使用一个随机的临时文件名。它也不再使用常见的文件markxxx.vcv。感谢Glenn
Sessions are now labelled using value of session time rather than numerically from 1 to largest session number in robust designs. Thanks to Tommy Garrison for this suggestion.
会话的会话时间标记值，而不是数字从1到最大会话数在强大的设计。感谢汤米驻军这个建议。
A bug was fixed in get.real which caused incorrect assignments of fixed parameter values in the unusual case where a fixed parameter had a non-zero
修正了在get.real造成分配固定的参数值不正确，在不寻常的情况下，一个固定的参数有一个非零
mark.wrapper was modified so it returns a list of the models that were constructed if run==FALSE. Thanks to Eldar Rakhimberdiev
mark.wrapper修改，以便它返回一个列表的模型，构建了如果运行== FALSE。由于埃尔达尔Rakhimberdiev
Code was added to extract.mark.output to extract deviance degrees of freedom. Thanks again to Eldar for
代码添加到extract.mark.output提取偏差自由度。再次感谢埃尔达尔为
A bug was fixed in make.mark.model that prevented use of sin link on within session parameters in a robust design model. Thanks to Tommy Garrison for reporting this bug.
修正了在make.mark.model罪的链接内，防止利用一个强大的设计模型的会话参数。感谢汤米驻军报告这个错误。
A bug was fixed in make.mark.model which prevented the use of time varying covariates with shared parameters. Thanks to Andre Breton for reporting
修正了在make.mark.model避免使用共享参数随时间变化的协变量。由于安德烈•布勒东的报告
simplify argument was removed from functions because I have not found a reason not to simplify and I have not been testing code with
从功能简化的参数，因为我没有理由不简化，我还没有测试代码
Version 2.0.7 (25 August 2011)
版本2.0.7（2011年8月25日）
Change to make.mark.model to fix bug in which mlogits were incorrectly assigned in ORDMS model when both Psi and pent used mlogit links. Thanks to Glenn Stauffer for identifying and tracking
更改为make.mark.model修复错误，其中的mlogits被不正确地分配ORDMS模型时，PSI和压抑mlogit链接。由于格伦斯托弗识别和跟踪
Fixed export.chdata and export.MARK so Nest survival models can be exported. Also changed default of argument ind.covariates to "all" which will use all individual covariates in the data in the file sent to MARK. Thanks
固定export.chdata和export.MARK所以巢生存模型可以出口。也改变了默认的参数ind.covariates“所有”，这将使用所有个人的协变量在文件中的数据发送到MARK。谢谢
Made change to process.data and mark to include a new argument reverse, which if set to TRUE with model="Multistratum" will reverse the timing of transition and survival. See mstrata for an
制造变化process.data和mark，包括一个新的论点相反，如果设置为TRUE，与模型=“多段”将扭转时间的过渡和生存。见mstrata为
Made change to make.design.data to allow for zero time intervals in non-robust design model. This was needed to allow use of the reverse time structure in multi-state models. In addition, for the reverse multistate model the function now adds an occasion (occ) field to the design data because the time field will be constant when with a 0 time interval. The row names of the design matrix and real parameters was extended for this model to include occasion (o) and occasion cohort (oc) to create unique labels because cohort and time are
变化make.design.data允许零的时间间隔不健壮的设计模型。这是必要的，允许使用的反向结构，多态模型。此外，对于的反向多态模型函数现在的场合（OCC）字段添加到设计数据，因为与0的时间间隔时，时间字段将是恒定的。行的设计矩阵和实时参数的名称，这个模型包括机会（O）和场合的队列（OC）来创建独特的标签，因为队列和时间延长
Version 2.0.6 (1
版本2.0.6（1
Change to MR resight examples so the output does not appear in notepad which was
切换到MR resight的例子，所以输出不会出现在记事本中，这是
Version
版本
Order of arguments for model.average.marklist were switched incorrectly such that ... was the second argument. This has been fixed to the original format where ... is at the end. This resulted in the value of any arguments other than the first to be ignored unless specifically named e.g., parameter="Phi". Thanks to Rod Towell for
model.average.marklist的参数顺序不正确的，这样切换...这是第二个参数。这已得到修复到原来的格式，其中...是在年底。这导致了第一个被忽略以外的任何参数值，除非特别命名的例如，parameter="Phi"的。由于杆Towell在
Additional changes were made to .First.lib to 1) examine any MarkPath setting, 2) look in C:/program files/mark or c:/program files (x86)/mark, 3) or to search the path. If MARK executable cannot be found in any of those ways then a warning is issued that the user needs to set MarkPath to the path specification for the location of the MARK executable. Thanks to Bryan
更多的变化。为1 First.lib）检查任何MarkPath的设置，2）看在C :/程序文件/标记或C :/程序文件（x86）/标记，3）或搜索路径。这些方法在任何，如果MARK可执行文件无法找到，然后发出警告的用户需要设置MarkPath，在MARK的可执行文件的位置的路径规范。由于Bryan
A bug in add.design.data was fixed where the function gave incorrect results in pim.type was anything other than "all". Thanks to Jeff Hostetler for reporting
中的bugadd.design.data是固定的功能了不正确的结果在pim.type的任何其他比“一切”。感谢杰夫Hostetler报告
The mark-resight models PoissonMR, LogitNormalMR, and IELogitNormalMR were added. This required some changes to make.mark.model,make.design.data and compute.design.data and the addition of an argument counts to process.data to provide mark-resight count data that are not in the capture history format. The format for counts is a named list of vectors (one group) or matrices (each group is a row) where the names of the list elements are specific to the model. Currently there is no checking to make sure these are named correctly. Some of these models are very sensitive to starting values; thus the use of initial values in the examples. Thanks to Brett
标记resight的模型PoissonMR，LogitNormalMR，并IELogitNormalMR的。这需要一些改变make.mark.model的，make.design.data和compute.design.data和另外的一个参数countsprocess.data，提供标记resight数数据不捕捉历史的格式。的格式counts是向量（1组）或矩阵（每一组是一排）中的列表元素的名称是特定于该模型的命名列表。目前还没有检查，以确保这些被命名为正确。一些这些模型是非常敏感的起始值;因此，在实施例中使用的初始值。感谢Brett
Version 2.0.4 (1 June 2011)
版本2.0.4（2011年6月1号）
Change made to .First.lib to check for availability of mark software that depends on operating system. It now provides a warning rather than stopping package attachment. This allows the user to set MarkPath to some location outside of default location Program Files or Program Files (x86) without changing path which requires administrator
进行的更改。First.lib检查标记依赖于操作系统的软件的可用性。它现在提供了一个警告而不是停止包附件。这允许用户设置MarkPath，不改变路径，这需要管理员以外的某个位置，默认位置的程序文件或程序文件（x86）的
Change made to run.mark.model to use shQuote because link
更改到run.mark.model使用shQuote的，因为链接
Version
版本
Now requires R 2.13
现在需要ŕ2.13
Change made to .First.lib to check for availability of mark software
所做的更改。First.lib的标志软件的可用性检查
Version 2.0.2 (16 May
版本2.0.2（5月16日
MarkPath no longer needs to be set if mark.exe is no longer in the default location (c:/Program Files/mark) but is specified in the path. The code now uses the R function Sys.which to find the correct location for mark.exe, if it is contained in the
MarkPath不再需要设置，如果mark.exe不再在默认位置（C :/ Program Files文件/符号），但中指定的路径。现在的代码使用R的功能Sys.which，以找到的正确位置mark.exe，如果它被包含在
Code for crm models was removed from RMark and moved to a different R package called marked that is under-development. This removes the FORTRAN code and accompanying dll and some functions and help files that were extraneous to RMark capabilities. There is still some code in some functions for crm that could be removed at some point. None of this matters to those who use RMark for its original purpose as an interface to
CRM模型的代码从RMark删除和移动到不同的R包称为标记，是发展不足。这消除了FORTRAN代码和相应的dll和一些功能和帮助文件的是多余的RMark能力的。还有一些代码在一些CRM的功能在某些时候可能会被删除。这件事没有使用RMark作为一个接口，它最初的目的
Many superficial changes were made to code so it could be posted on CRAN. Three changes that may be noticed by users involved renaming deriv.inverse.link, summary.ch and merge.design.covariates to deriv_inverse.link, summary_ch, and merge_design.covariates. These names conflicted with the generic functions deriv, summary and merge. It is only the last 2 that you may have in your scripts and you will have to rename them. The deprecated function merge.occasion.data was removed. Sorry for any
许多肤浅的代码进行了更改，因此它可以被张贴在CRAN。三个变化，可能会注意到，用户参与的的重命名deriv.inverse.link，summary.ch和merge.design.covariates deriv_inverse.link，summary_ch，merge_design.covariates。这些名称相冲突的一般职能DERIV，汇总和合并。这是唯一的，最后的2，你可能已经在你的脚本，你必须重命名。已过时的的功能merge.occasion.data被删除。对不起，任何
The dependency on Hmisc for the
依赖于Hmisc
Version 2.0.1 (21 Feb 2011)
版本2.0.1（2011年2月21日）
Made a change to run.mark.model to handle output
改变run.mark.model处理输出
Added an argument prefix in mark, run.mark.model and cleanup. Like other parameters for mark, it can also be used in mark.wrapper as one of the ... arguments. Previously the mark files have always been named "marknnn.*". By specifying prefix you can now create sets of models with different prefixes. For example, prefix="cu" would result in cu001.*(cu001.out, cu001.inp, etc), cu002.* etc. This provides the ability to name files to do things like naming them based on the species being analyzed. In general, there is no need to work with these files directly because the filename.* is stored with each mark object and the various R functions use that link to provide the information from the files. If you use prefixes other than "mark", you'll need to call call cleanup with each prefix to remove unused files. See run.mark.model for an example that shows use of the prefix argument to split the dipper data into separate analyses for each sex. Note that use of prefix was not mandatory here to separate the analyses
添加参数prefixmark，run.mark.model和cleanup。喜欢的其他参数mark，它也可以被用来在mark.wrapper为一体的...参数。以前的标志文件被命名为“marknnn。*”。通过指定prefix，“你现在可以创建模型集，不同的前缀。例如，prefix="cu"将导致cu001。*（cu001.out，cu001.inp等），cu002。*等，这提供了文件名命名的物种正在分析的基础上做这样的事情的能力。在一般情况下，没有必要直接使用这些文件，因为存储的文件名。*每一个mark对象和不同的R函数使用链接提供的文件中的信息。如果您使用前缀以外的“标记”，你会需要调用调用cleanup，每个前缀删除未使用的文件。见run.mark.model一个例子，说明使用的前缀参数分裂单独分析的的瓢数据，为每个性别。请注意，使用的前缀的时间是在这里不是强制性的分离分析
Additional usefulness has been coded for argument initial for assigning initial values to beta parameters. Previously, the options were either a vector of the same length as the new model to be run or a previously run model in a mark object from which equivalent betas are extracted based on their names in the design matrix. Now if the vector contains names for the elements they will be matched with the new model like with the model option for initial. If any betas in the new model are not matched, they are assigned 0 as their initial value, so the length of the initial vector no longer needs to match the number of parameters in the new model as long as the elements are named. The names can be retrieved either from the column names of the design matrix or from rownames(x$results$beta) where
额外的用处已经被编码为的参数initial测试参数的初始值。此前，选项可以具有相同的长度的矢量作为新的模型运行或先前运行的模型在mark对象的基础上，其名称在设计矩阵提取从该等效测试版。现在，如果向量包含的元素的名称，他们将匹配等新模式的初始模型的选择。如果任何测试版的新模式不匹配，他们被分配作为其初始值0，这样的长度initial向量不再需要的参数的数量相匹配的新模式，只要元素是命名。无论是从设计矩阵的列名或从rownames(x$results$beta)其中的名称可以检索
Using the feature above, I added a new argument use.initial to mark.wrapper. If use.initial=TRUE, prior to running a model it looks for the first model that has already been run (if any) for each parameter formula and constructs an initial vector from that previous run. For example, if you provided 5 models for p and 3 for Phi in a CJS model, as soon as the first model for p is run, in the subsequent 2 models with different Phi models, the initial values for p are assigned based on the run with the first Phi model. At the outset this seemed like a good idea to speed up execution times, but from the one set of examples I ran where several parameters were at boundaries, the results were discouraging because the models converged to a sub-optimal likelihood value than the runs using the default initial values. I've left
使用上述功能，我添加了一个新的参数use.initial到mark.wrapper。如果use.initial=TRUE，运行之前，它看起来的第一款车型，已经运行（如果有的话）的每个参数公式，并构建了一个initial向量，以前运行的一个模型。例如，如果提供了5种型号的p和3披CJS模型中，尽快的p的第一模型运行时，在随后的2款与不同披模型，对于p的初始值的基础上，分配运行披模型。在开始，这似乎是一个好主意，加快执行时间，但是从一组例子，我跑了几个参数的边界处，结果令人沮丧，因为这些模型融合到一个次优的似然值比运行时使用默认的初始值。我已经离开
A possibly more useful argument and feature was added to mark.wrapper in the argument initial. Previously, you could use initial=model and it would use the estimates from that model to assign initial values for any model in the set defined in mark.wrapper. Now I've defined initial as a specific argument and it can be used as above but you can also use it to specify a marklist of previously run models. When you do that, the code will lookup each new model to be run in the set of models specified by initial and if it finds one with the matching name then it will use the estimates for any matching parameters as initial values in the same way as initial=model does. The model name is based on concatenating the names of each of the parameter specification objects. To make this useful, you'll want to adapt to an approach that I've started to use of naming the objects something like p.1,p.2 etc rather than naming them something like p.dot, p.time as done in many of the examples. I've found that using numeric approach is much less typing and cumbersome rather than trying to reflect the formula in the name. By default, the formula is shown in the model selection results table, so it was a bit redundant. Now where I see this being the most benefit. Individual covariate models tend to run rather slowly. So one approach is to run the sequence of models (eg results stored in initial_marklist), including the set of formulas with all of the variables other than individual covariates. Then run another set with the same numbering scheme, but adding the individual covariates to the formula and using initial=initial_marklist That will work if each parameter specification has the same name (eg., p.1=list(formula=~time) and then p.1=list(formula=~time+an_indiv_covariate)). All of the initial values will be assigned for the previous run except for any added parameters (eg. an_indiv_covariate)
一个可能有用的参数和功能已添加到mark.wrapper的说法initial。在此之前，你可以使用initial=model和分配初始值的任何模型中定义的集合中mark.wrapper，它会使用该模型的估计。现在，我已经定义了initial作为一种特定的参数，它可以被用作上面，但你也可以用它来指定一个marklist以前运行的模型。当你这样做时，代码会查找每一个新的模式来运行在指定的initial，如果它找到一个相匹配的名字，然后它会使用任何匹配的参数作为初始值估计的模型集相同的方式initial=model。的型号名称是根据串联每个参数规范对象的名称。为了使这个有用的，你要适应的做法，我已经开始使用命名对象类似第1页，第2页等，而不是命名类似p.dot，p.time所做的那样在许多实施例。我发现，用数字的方法要少得多打字和繁琐的，而不是试图以反映公式中的名称。默认情况下，该公式模型中的选择结果表所示，所以这是一个有点多余。现在，我看到这是最大的利益。个人的协变量的模型往往会运行比较缓慢。因此，一种方法是运行序列模型（如结果存储在initial_marklist），包括一套公式，所有的变量不是个别的变量。然后运行另一组具有相同编号的计划，但将个人变项的公式和使用initial=initial_marklist这将工作，如果每个参数的规范具有相同的名称（例如，第1页=列表（公式=~时间），然后第1页=列表（公式=~时间+ an_indiv_covariate））。所有的初始值将被分配为先前运行的任何附加的参数（如an_indiv_covariate除外）
I added a new function search.output.files to the set of utility functions. This can be useful to search all of the output files in a marklist for a specific string like "numerical convergence suspect" or just "WARNING". The function returns the model numbers in the marklist that contain that string in the output
我添加了一个新功能search.output.files的实用功能。这可能是有用的，搜索所有的输出文件在marklist一个特定的字符串，如“收敛犯罪嫌疑人”或“警告”。该函数返回的型号在marklist包含该字符串的输出
Further changes were needed to popan.derived to handle data that are summarized (i.e. frequency of capture history >1). Thanks to Carl Schwarz for reporting and finding the change
需要进一步的修改，popan.derived处理，汇总的数据（即频率捕捉历史> 1）。由于卡尔·施瓦茨的报告和发现的变化
A bug was fixed in create.dm was fixed so it would return a matrix instead of a vector
修正了在create.dm是固定的，所以它会返回一个矩阵，而不是一个向量
Version 2.0.0 (14 Jan 2011)
版本2.0.0（2011年1月14日）
The packages msm, Hmisc, nlme, plotrix are now explicitly required to install RMark. These were used in examples or for specialty functions, but to avoid
包男男性接触者，Hmisc，NLME，plotrix明确要求安装RMark。这些示例中使用的或专业的功能，但要避免
Added example for "CRDMS" model that was created by Andrew
添加了示例“CRDMS”的模式，是由安德鲁
Change was made for gamma link in v1.9.3 was only made to Pradel model and not Pradsen like it stated. Both now correctly use the logit link as the default for gamma. Thanks to Gina
更改为伽玛链接在v1.9.3，才向普拉德尔模型，而不是像它说的Pradsen。无论是现在正确地使用作为默认的伽玛logit的关联。由于吉娜
Change was made in make.mark.model that prevented use of groups with Nest survival models. Thanks to Jeff
变化是在make.mark.model的群体与鸟巢的生存模型，阻止使用。感谢Jeff
Change was made in make.design.data because re-ordering of parameters caused issues with the CRDMS model because the subtract.stratum were not being
make.design.data因为重新排序参数引起的问题的CRDMS模型，因为subtract.stratum不被改变，是在
Version 1.9.9 (2 Nov 2010)
版本1.9.9（2010年11月2日）
This version was built with R 2.12 and will not work with earlier versions of R. It contains both 32 and 64 bit versions and R will automatically
这个版本是建立与R 2.12，并不会与早期版本的R.它包含32位和64位版本和R会自动
Parameter ordering for some models (RDHet, RDFullHet, RDHHet, RDHFHet, OccupHet, RDOccupHetPE, RDOccupHetPG, RDOccupHetEG, MSOccupancy, ORDMS, and CRDMS) had to be changed such that the models could be imported into the MARK interface. This change can influence any code you have written for those models if you specified parameter indices because the ordering of the parameters were changed. For example, see change in example for RDOccupancy to use indices=c(1) from c(10). Thanks to Gary White for
某些型号的参数排序（RDHet，RDFullHet，RDHHet，RDHFHet，OccupHet，RDOccupHetPE，RDOccupHetPG，RDOccupHetEG，的MSOccupancy，ORDMS，CRDMS），就必须改变这样的模型可以导入到MARK接口。这种变化可以影响你写的，如果你指定的参数指标，因为这些模型的参数的顺序改变任何代码。例如，改变例如RDOccupancy使用指数= C（1）C（10）。由于加里·白
Modified code in extract.mark.output to handle cases with more than 9999 real parameters because MARK outputs ****
修改后的代码在extract.mark.output处理的情况下，与超过9999个实际参数，因为MARK输出****
Version 1.9.8 (15 Sept 2010)
版本1.9.8（2010年9月15日）
Added model="CRDMS" with parameters S, Psi, N, p, and c for closed robust design
添加model="CRDMS"参数PSI，S，N，P，c为封闭的坚固的设计
Patched popan.derived which produced incorrect abundance estimates with unequal time intervals. Thanks to Andy Paul for finding this error and testing for me.
修补popan.derived产生不正确的丰度估计不相等的时间间隔。感谢安迪·保罗发现这个错误，并测试对我来说。
Patched export.MARK which failed for robust design models. Thanks to Dave Hewitt and Gary
破旧的export.MARK没有强大的设计模式。由于戴维·休伊特和加里
Version 1.9.7 (14 April 2010)
版本1.9.7（2010年4月14日）
Added model="Brownie" with parameters S and f which is the Brownie et al. parameterization of the recovery model. "Recovery only" (in RMark) model="Recovery" which is also encounter type "dead" in MARK uses the Seber parameterization with parameters S and r which is also used in the models for live and dead encounter
增补model="Brownie"参数S和f是布朗尼等人。参数化的恢复模式。 “恢复”（在RMark）model="Recovery"也遇到类型“死”在MARK使用Seber参数与参数S和r，它也被用来在模型中的活的和死的相遇
Added model="MSLiveDead" with parameters S, r, Psi and p. It is the multistate version
加入model="MSLiveDead"S参数，R，PSI和p。这是多态版本
Added compute.Sn to utility functions for computation of natural survival from total survival when all harvest is reported. Patched nat.surv which was incorrectly rejecting based on model type.
添加compute.Sn计算的报告时，所有的收获是自然生存，总生存期的实用功能。修补nat.surv这是不正确地拒绝根据模型类型。
Added var.components.reml to provide an alternate variance components estimation using REML or maximum likelihood. It allows a random component that is not iid which is all that var.components
加入var.components.reml提供的备用方差分量估计使用REML或者最大似然。它允许没有独立同分布的随机成分，这是所有var.components
Replaced all T/F values with TRUE/FALSE to
代替所有的T / F值TRUE / FALSE
Version 1.9.6 (1 February 2010)
版本1.9.6（2010年2月1日）
Writing the popan.derived function has led me down all sorts of paths. I had to make one small change to this function to handle externally saved models. However, various changes listed below were brought on by using this function with a relatively large POPAN model.
写popan.derived功能，导致我所有的路径。我不得不做出一个小的变化，这个函数来处理外部保存的模型。然而，以下所列的各种变化所带来的具有相对大的POPAN模型使用此功能。
Most importantly I discovered an error in computations of real parameters with an mlogit link in which some of the real parameters involved in the mlogit link were fixed. This is NOT a problem if you simply used the real parameter values extracted from MARK; however, if you were using either compute.real (model.average uses this function) or covariate.predictions to compute those real parameters (with an mlogit link) then they may be incorrect. This would have been apparent because their value would have changed relative to the original values extracted from the MARK output. Correcting this error involved changes in compute.real, convert.link.to.real and covariate.predictions to correct the real parameter estimates and their standard errors. I've not found it in the MARK documentation but deduced that if you use the mlogit link and fix real parameters it uses those fixed real parameter values in the calculation. A simple example will make it clear. Consider pent for 5 occasions where the first is computed by subtraction and you then have 4 real parameters. Let's assume that the 3rd and fourth parameters were fixed to 0. Then the real parameters are calculated as follows: pent2=exp(beta2)/(1+ exp(beta2)+exp(beta3)+exp(0)+exp(0)), pent3=exp(beta3)/(1+ exp(beta2)+exp(beta3)+exp(0)+exp(0)), pent4=0, pent5=0 and pent1=1-pent2-pent3-0-0 (in this case). Obviously you would not want to fix any real parameters to be >1, <0 or to have the sum to be <0 or >1. This structure also had implications on how the standard error was calculated.
最重要的是，我发现了一个错误，在计算中的实际参数与mlogit链接，在一些参与的mlogit链接的真正的参数是固定的。这不是一个问题，如果你只是用真实的参数值提取MARK，但是，如果你使用的是compute.real（model.average使用此功能）或covariate.predictions计算那些真正的参数（ mlogit链接），那么他们可能是不正确的。这将是明显的，因为它们的值会改变相对于从MARK输出提取的原始值。纠正这个错误涉及改变compute.real，convert.link.to.real和covariate.predictions纠正的真实参数估计值及其标准误差。我还没有发现它的MARK文件，但推断，如果您使用mlogit的链接和解决实际参数在计算中使用这些固定的参数值。一个简单的例子说清楚。考虑被压抑的5次，其中第一个是由减法计算，你有4个实际参数。让我们假设，在第三和第四个参数被固定为0。真正的参数的计算方法如下：戊-2 = exp（β2）/（1 + EXP（β2），pent3 + EXP（beta3版）+ EXP（0）+ EXP（0））= exp（beta3版）/（1 +进出口（β2）+进出口（素β3）+进出口（0）+进出口（0）），pent4 = 0，pent5 = 0和pent1 = 1 - 戊-2 - pent3-0-0（在这种情况下）。很显然，你不会想解决任何实际的参数> 1，<0或<0或> 1的总和。这种结构也有如何计算的标准误差的影响。
In addition the coding was made more efficient in covariate.predictions for the case where data(index=somevector) is used without any data entries for covariate values in the design matrix. While the task performed with that use of the function could be done with compute.real, it is useful to have the capability in covariate.predictions as well because it will then model average over the listed set of parameters. The previous approach to coding was inefficient and led to very large matrices that were unnecessary and could cause failure with insufficient
此外，编码更有效地covariate.predictions的情况下data(index=somevector)使用，没有任何数据项在设计矩阵的协变量值。虽然执行的任务，使用的功能，可以做compute.real，它是有用的，有能力在covariate.predictions好，因为它会列出的参数型号平均。以前的编码方法效率低，导致非常大的矩阵，是不必要的不足，并可能导致失败
Calculation of NGross was added to popan.derived and logical arguments N and NGross were added to control what was computed in the call. In addition, argument drop was added which is passed to covariate.predictions to control whether models are dropped when variance of betas are not all
计算加入的NGross的popan.derived和逻辑论证N和NGross被添加到控制计算在调用的。此外，参数drop这是通过covariate.predictions来控制是否被丢弃模型方差的测试版时，是不是所有的
var.components was modified to use qr matrix inversion. The returned value for beta is now a dataframe that includes the std errors which are extracted from the vcv matrix. Also, if the design matrix only uses a portion of the vcv matrix, the appropriate rows and columns are now extracted. Prior to this change, the standard errors would have been unreliable if the design matrix didn't use the entire set
var.components被修改为使用QR矩阵求逆的β返回的值是一个数据框，其中包括性病的错误中提取的VCV矩阵。此外，如果仅使用设计矩阵的VCV矩阵的一部分，将适当的行和列正在提取。在此之前的变化，标准差已经不可靠的，如果设计矩阵没有使用整套
Version 1.9.5 (4 December
版本1.9.5（12月4日
A bug in covariate.predictions was fixed that would assign fixed values incorrectly if the parameter indices were specified in anything but ascending order. The error would have been obvious to anyone that may have encountered it because estimated parameters would likely have been assigned a fixed value. In most cases indices would be passed in order if they were selected from the design data unless indices were chosen from more than one parameter type. I discovered it using the popan.derived function I added in v1.9.4 because it requests indices for multiple parameters in a
中的bugcovariate.predictions是固定的，会分配固定的值不正确如果参数指标中指定的任何东西，但升序排列。该错误将是显而易见的任何人，可能会遇到，因为估计的参数可能会被分配一个固定的值。在大多数情况下，指数命令，如果他们选择的从设计数据，除非指数选择从一个以上的参数的类型，将被传递。我发现它使用popan.derived“的功能，我在v1.9.4增加，因为它请求指数中的多个参数
Version 1.9.4 (6 November 2009)
版本1.9.4（2009年11月6日）
Note that this version was built with R 2.10 which no longer supports compiled help files (chtml). If you were using compiled help files to get help with RMark, you'll need to switch to regular html files by using options(help_type="html") in R. You can put this command in your RProfile.site file so it is set up that way each time you start R. The functionality is the same but it is not as pretty. You can find the index (what used to be in a window on the left) as a link at
需要注意的是建立这个版本不再支持编译的帮助文件（CHTML）与R 2.10。如果你使用的编译帮助文件，以获得帮助RMark，你需要切换到普通的HTML文件中使用选项（help_type =“HTML”），R.所以你可以把这个命令在您的RProfile.site文件设立这样在每次启动R.的功能是一样的，但它是不漂亮。一个链接，您可以找到索引（以前是在一个窗口的左边）
Changed export.MARK so it will not allow selection of a project name that would over-write an existing .inp
改变export.MARK，所以它不会允许选择的项目名称会超过现有的写。INP
Added the function popan.derived which for POPAN models computes derived abundance estimates by group and occasion and sum of group abundances for each occasion. For some reason RMark is unable to extract all of the derived parameters from the MARK binary file for POPAN models. This function provides the derived abundance estimates and their var-cov matrix and adds the abundance estimate sum across groups for each occasion which is not provided by MARK. Note that by default confidence intervals are based on a normal distribution to match the output of MARK, but if you want log-normal intervals use
新增的功能popan.derived组和场合组每次丰度和POPAN模型计算得出的丰度估计。对于某种原因，RMark是无法提取的派生参数从MARK二进制文件POPAN模型的所有。此功能提供了衍生的丰度的估计及其变种病毒矩阵和增加了丰富的估计，各组每次不提供MARK总和。请注意，默认情况下，置信区间的一个正态分布的基础上，以匹配输出的MARK，但如果你想记录正常的时间间隔使用
The model.average.list and model.average.marklist functions were modified to use revised estimator for the unconditional standard error (eq 6.12 of Burnham and Anderson (2002)) which is now the default in MARK. To use eq 4.9 (the prior formula) set the argument revised=FALSE.
model.average.list和model.average.marklist函数进行了修改，修订估计为无条件的标准误差（式6.12伯纳姆和安德森（2002年）），这是目前默认情况下，MARK。使用EQ 4.9（事先公式）的参数设置revised=FALSE。
Fixed bug in model.average.list which in some cases failed when the list of var-cov matrices
修正了在model.average.list失败时，在某些情况下，VAR-CoV的矩阵列表
Code in model.average.marklist was changed to set standard error to 0 if the variance is negative. The same is done in the var-cov matrix for the variance and any corresponding covariances. The results from RMark will now match the model average results from MARK for this case. It is not entirely clear that this is the
代码model.average.marklist改变设置标准误差的方差为0，如果是负的。同样是做任何相应的方差和协方差为的VAR-CoV的矩阵中。将匹配的结果RMark MARK这种情况下，模型的平均结果。这是不完全清楚，这是
Changed code in cleanup to handle case in
更改后的代码cleanup处理情况
Changed use of grep and regexpr in convert.inp and extract.mark.output to accomodate change in R.2.10. The code should work in earlier versions of R
改变使用grep和regexprconvert.inp和extract.mark.output，以适应在R.2.10变化。的代码应该在早期版本的R
Created a function adjust.value and kept special case of adjust.chat. For any field other than chat it will adjust the value in model$results. As an example, to adjust the effective sample size (ESS) use model.list=adjust.value("n",value,model.list) where value is replaced with the ESS you want to use. As part of the change model.table was changed
创建一个函数adjust.value和保持特殊情况下，adjust.chat。以外的其他任何领域chat将调整值在model$results。作为一个例子，调整使用model.list=adjust.value("n",value,model.list)值将被替换的ESS，你要使用有效样本数（ESS）。的变化model.table改变
Version 1.9.3 (24 September 2009)
版本1.9.3（2009年9月24日）
Default link function for Gamma in the Pradel seniority model had been incorrectly set to log and has now been changed to logit to restrict it to be a
默认链接的功能伽玛中的普拉德尔的资历模型被错误地设置为登录，现在已被更改为罗吉特限制这是一个
A bug was fixed in compute.real and covariate.predictions in which confidence intervals were being incorrectly scaled by c (chat adjustment) instead of sqrt(c). The reported standard errors were correctly using sqrt(c) and only the confidence intervals for the real predictions were too large. Simply re-running the prediction computations for a model will provide the correct results. There is no reason to re-run the models. Also this in no way affects
修正了在compute.real和covariate.predictions置信区间C（聊调整），而不是的SQRT（三）被错误地缩放。报告的标准误差正确使用SQRT（c）和过大的置信区间的实时预测。只需重新运行的模型的预测计算提供正确的结果。我们没有理由重新运行模型。此外，这丝毫不影响
A related bug was fixed in compute.real and covariate.predictions which created invalid confidence intervals for real parameters if a probability link other than logit was used and a single type of link
与此相关的错误被固定在compute.real和covariate.predictions创建真正的参数，如果无效的置信区间的概率链接以外罗吉特使用单一类型的链接
Version
版本
Added the function export.MARK which creates a .Rinp, .inp and optionally renames one or more output files for import to MARK. The July 2009 version of MARK now contains a File/RMARK Import menu item which will automatically create the MARK project using the information in these files. This prevents problems that have been encountered in creating MARK projects with RMark output because the data/group structures are setup exactly in MARK as they were in RMark. See export.MARK for an
增加了功能export.MARK创建一个。RINP，inp和选择性重命名一个或多个输出文件导入标记。 2009年7月版MARK包含文件/ RMARK导入“菜单项，它会自动创建MARK项目中使用这些文件中的信息的。这可以防止MARK项目RMark输出时所遇到的问题，，因为在MARK的数据/组结构设置完全，因为他们在RMark。见export.MARK为
Fixed a problem in make.design.data which prevented use of remove.unused with unequal time intervals and more
修正了一个问题，在make.design.data防止使用remove.unused不相等的时间间隔和
At least one person has encountered a problem with a very large number of parameters in which RMark created the input file with PIMs written in exponential notation for the larger indices. MARK will not accept that format and it will fail. The solution to this is to set the R option scipen to a positive number.
至少有一人遇到了一个问题，有一个非常大的参数中，RMark创建的输入文件与PIM指数符号写在较大的指数。 MARK不会接受的格式，它将会失败。这个问题的解决办法是设置的的R选项scipen到一个正数。
Version 1.9.1 (2 June 2009)
版本1.9.1（2009年6月2日）
Fixed a problem make.design.data which was not
修正了一个问题make.design.data这是不
Made a change in export.chdata like the change in make.mark.model to accomodate
做了更改，在export.chdata一样的变化make.mark.model，以适应
Made a change in process.data so that strata.labels can be specified for Multistrata designs like with ORDMS so an unobserved strata can be
做了更改，在process.data所以strata.labels可以被指定为多层次设计喜欢与ORDMS的，所以一个未观察到各阶层可以
A warning was added to the help file for export.chdata and export.model so it is clear that the MARK database must be created correctly and with the .inp file created by export.chdata from the processed data that was used to create the models that are being exported. This is to ensure that the group structure is setup such that the assumed model structure for groups
一个警告被添加到export.chdata和export.model的帮助文件，所以很清楚，必须建立正确的MARK数据库和从处理过的数据。inp文件中创建的export.chdata用于创建模型已出口。这是为了确保该组结构设置等，假设的模型结构组
Version 1.9.0 (30 April 2009)
版本1.9.0（2009年4月30日）
Fixed a bug in summary.mark which occasionally produced
修正了一个错误summary.mark偶尔产生
Made a change in make.mark.model to accomodate
make.mark.model，以适应改变
RMark now
RMark现在
Version 1.8.9 (9
版本1.8.9（9
Changed model.average.marklist and covariate.predictions to set NaN or Inf results in v-c matrix to 0 to cope with poorly determined models. Also, for each function the dropping of models is now restricted to cases in which there are negative variances for the betas being used in the averaged parameter estimates. Unused betas are ignored. For example, if model.average is called with parameter="Phi", then the model will only be dropped if there is a negative variance for one of the
改变model.average.marklist和covariate.predictions设置在vc矩阵NaN或Inf结果为0，以配合不好确定模型。此外，对于每个函数模型的丢弃限制的情况，其中有负差异的测试版正在使用中的平均参数估计。未使用的测试版将被忽略。例如，如果model.average被称为parameter="Phi"，那么模型将只被丢弃，如果有一个负的之一的方差
In var.components the tolerance value (tol) in the call to uniroot was reduced to 1e-15 which should provide better estimates of the process variance when it is small. Previously a process
在var.components的公差值（tol）在调用到uniroot减少到1E-15，可提供更好的估计制程变异时，它是小。过去曾是一个过程
Made changes to cleanup, coef.mark, and make.mark.model to accomodate externally
进行了修改cleanup，，coef.mark和make.mark.model，以适应外部
Version
版本
An error was fixed in make.time.factor which created incorrect assignments when only some of the time dependent variables contained a "." for occasions with no
make.time.factor创造了不正确的分配随时间变化的变量时，只有一些包含一个“。”的场合，没有固定在了一个错误
Patched compute.design.data which was not creating the design data in the same order as the PIM construction for the newly added ORDMS
修补compute.design.data这是不以相同的顺序创建的设计数据，作为的PIM建设为新添加的ORDMS
Generalized section of code in make.mark.model to handle mlogit
广义部分中的代码make.mark.model处理的mlogit
Fixed a bug in process.data in which the initial ages were not correctly assigned in some situations with multiple grouping variables. Note that it is always a good idea to examine the design data after it is created to make sure it is structured properly because it relates the data and model structure via the grouping variables and the pre-defined variables (ie age, time etc), While I've done a lot of testing, I have certainly not tried every possible example and there is always the potential for an error to occur in a circumstance that I've not
修正了一个在process.data中的初始年龄不正确地分配在某些情况下，与多个分组变量。请注意，它始终是一个好主意，检查数据后，它被创建，以确保它是正确的结构，因为它涉及的数据和模型结构，通过分组变量和预定义变量（如年龄，时间等）的设计，虽然我已经做了很多的测试，我肯定不会想尽一切可能的例子，总有潜在的错误发生在一个情况下，我已经不
Version 1.8.7 (13 November 2008)
版本1.8.7（2008年11月13日）
An argument common.zero was added to function make.design.data and compute.design.data. It can be set to TRUE to make the Time variable have a common time origin of begin.time which is useful for shared parameters like p and c in closed capture
的论据common.zero被添加到功能make.design.data和compute.design.data。它可以被设置为TRUETime变量都有一个共同的时间原点begin.time这是有益的共享参数，如p和c在封闭的捕获
The function read.mark.binary was patched to work with
的功能read.mark.binary修补工作
The model type ORDMS for open robust design multi-state models was added. An example data set will be added at a later date after further testing has been
该模型类型ORDMS开放的强大的设计多态模型。的一个例子的数据集将被添加在稍后的日期后，进一步的测试已经
Some patches were made to fix some aspects of profile intervals and to fix adjustment by chat in summary.mark when showall=F. The notation for profile intervals is now included in the field model$results$real$note where model is the name of a mark model. Previously an incomplete notation was kept in model$results$real$fixed but that field is now used exclusively to denote fixed parameters. It is important to realize that profile intervals computed by MARK are only found in model$results$real$note and are not changed by a chat adjustment unless the model is re-run. None of the intervals computed by RMark and displayed
有些补丁来修复某些方面的配置文件的时间间隔，并修复调整的聊天summary.markshowall=F。配置文件的时间间隔中包含的字段的符号model$results$real$note其中model的名称标记模型。以前，一个不完整的符号被保存在model$results$real$fixed“可是那场现在是专门用来表示固定的参数。重要的是要实现该配置文件的时间间隔计算的MARK才发现model$results$real$note的chat调整，并没有改变，除非重新运行模型。没有计算的RMark和显示的时间间隔，
Version 1.8.6 (28 October 2008)
版本1.8.6（2008年10月28日）
A bug in an error message for initial.ages in
initial.ages在一个错误的错误消息
A new function var.components was added to provide variance components capability as in the MARK interface except that shrinkage estimators are not
一个新的函数var.components添加到方差分量的能力在MARK接口的，除了收缩估计是不
Fixed parameter values are now being reported correctly by covariate.predictions. Also over-dispersion (c>1) was not being included in the variances for
固定的参数值，现在出现了正确的covariate.predictions。另外过度分散（三> 1）不被包括在的方差
Some utility functions were added including pop.est,nat.surv, and
增加了一些实用功能，包括pop.est，nat.surv，
The function model.average has been changed to a generic function. Currently it supports 2 classes: 1) list, and 2) marklist. The latter was the original model.average which has been renamed model.average.marklist and the first argument has been renamed x instead of model.list to match the standard generic function approach. The previous syntax model.average(...) will work as long as the usage does not name the first agument as in the example model.average(model.list=dipper.results,...). The list formulation (model.average.list) was created to enable a generic model averaging of estimates instead of just real parameter estimates from a mark model. It could be used with any set of estimates, model weights and estimates of precision.
函数model.average已更改为一个通用的功能。目前，它支持2类：1）名单，和2）marklist。后者是原model.average已更名为model.average.marklist的第一个参数已更名为x而不是model.list的相匹配的标准的通用功能的方法。以前的语法model.average(...)将工作，只要使用没有名字的第一个agument的例子model.average(model.list=dipper.results,...)。名单制定（model.average.list）的设立是为了使从mark模型的通用模型，而不是仅仅实时参数估计值的平均估计。它可以被用来与任何一组的估计，模型的权值和估计的精度。
A change is needed to read.mark.binary to accomodate the change to mark.exe with the version dated 1 Oct 2008. Some data types (notably Nest survival) may not work with the new version of mark.exe. Working with Gary to make the patch. If you need an older version of mark.exe contact
需要改变read.mark.binary，以适应变化的版本于2008年10月1日mark.exe。新版本的mark.exe某些数据类型（特别是鸟巢生存）可能无法正常工作。工作与加里的补丁。如果你需要一个较旧的版本的mark.exe接触
Version 1.8.5 (8 October 2008)
版本1.8.5（2008年10月8日）
A bug in process.data was fixed that prevented use of a dataframe contained in a list while
中的bugprocess.data固定，防止使用一个数据框的列表中，而
Profile intervals on the real parameters can now be obtained from MARK using the arguments profile.int and optionally chat in mark. The argument profile.int can be set to TRUE and a profile interval will be constructed for all real parameters, or a vector of parameter indices can be specified to restrict the profiling to certain parameters. The value specified by chat is passed
现在可以得到真正的参数的配置文件的间隔，从标志使用的参数profile.int和可选chatmark。参数profile.int可以设置为TRUE和一个配置文件的时间间隔将构建所有的实际参数，可以指定的向量参数指标限制对某些参数的分析。指定的值chat传递
References to cjs, js etc have been removed from here because this code was
参考CJS，JS等已被删除，因为这段代码是从这里开始
Yet another fix to summary.ch which gave incorrect results for the number recaptured at least once when marray=F and the data contained non-unity values for freq.
另一种修复summary.ch数夺回了不正确的结果至少一次，当marray=F和包含的数据不统一价值观freq。
Version 1.8.4 (29 August 2008)
版本1.8.4（8月29日）
A generic function coef.mark was added to extract the table of betas from the model with the expression coef(model) where model is a mark model that has been run and contains output. The table includes standard errors and confidence
一个通用的函数coef.mark的表达加入从模型中提取表的测试版coef(model)model是mark模式，已经运行，并包含输出。该表包括标准误差及置信
An argument brief was added to summary.mark. If brief=TRUE the real
的论据brief加入summary.mark。如果brief=TRUE
References to cjs, js etc have been removed from here
参考文献CJS，JS等已被删除从这里开始
A bug in summary.ch was fixed. It would produce erroneous results when the data contained a non-constant freq field. Results with the default of
中的bugsummary.ch是固定的。它会产生错误的结果的数据时，包含了非恒定freq字段。默认的结果
The function adjust.chat and its help file were changed such that it was clear that a model.list argument
的功能adjust.chat和它的帮助文件发生了变化，很明显，model.list参数
Version 1.8.3 (25 July 2008)
版本1.8.3（7月25日）
For robust design models, an error trap was added to process.data to make sure that the capture history length matches the specification for the time.intervals. This error was already trapped
强大的设计模型，错误陷阱到process.data，以确保捕捉历史的长度规格相匹配的为time.intervals。这个错误已经被困
Fixed an error in make.mark.model that prevented interaction model of session/time-specific individual covariates in a
修正了一个错误make.mark.model，防止交互模型的会话/时间特定的个体协变量的
Fixed an error in process.data so that the field freq
修正了一个错误process.data“这样的领域freq
print.mark was modified to add an argument input which if set to input=TRUE will have the MARK input file be displayed rather than the output file. Also, wait=FALSE was set in the system command which means the viewer window will be opened and you can carry on with R. Before you had to close the
print.mark进行了修改，添加一个参数input设置为input=TRUE将有MARK输入文件的输出文件，而不是显示。此外，wait=FALSE设置在系统命令，这意味着浏览器窗口将被打开，你可以进行与R.之前，你必须关闭
An example RDOccupancy provided by Bret Collier was added for the Robust Occupancy model which shows the use of session and time-varying individual covariates in a
一个例子RDOccupancy由Bret科利尔加入显示了使用会话和个人随时间变化的协变量在模型的鲁棒入住
Version 1.8.2 (26 June 2008)
版本1.8.2（2008年6月26日）
summary.ch was modified to allow missing cohorts (no captures/recaptures) for an occasion and to fix a bug in which bygroup=FALSE
summary.ch缺失的人群（捕获/夺回）进行了修改，允许一个场合，并修复一个错误，其中bygroup=FALSE
To avoid running out of memory, an argument external has been added to collect.models, mark, rerun.mark, and run.mark.model. As with all arguments of mark, external can also be set in mark.wrapper. Likewise, external can also be set in run.models and it is passed to run.mark.model. The default is external=FALSE but if it is set to TRUE then the mark model object is saved in an external file with an extension .rda and the same base filename as its matching MARK output files. The mark object in the workspace is a character string which is the name of the file with the saved image (e.g., "mark001.rda"). If external=TRUE with mark.wrapper then the resulting marklist contains a list entry for each mark model which is only the filename and then the last entry is the model.table. All of the functions recognize the dual nature of the mark object (i.e., filename or mark object) in the workspace. So even if the mark object only contains the filename, functions like print.mark or summary.mark will work. However, if you have used external=TRUE and you want to look at part of a mark object without using one of the functions, then use the function load.model. Whereas, before you may have typed mymark$results, if you use external=TRUE, you would replace the above with
为了避免耗尽内存，参数external已加入collect.models，mark，rerun.mark和run.mark.model。至于所有参数的mark，external也可以设置在mark.wrapper。同样，external也可以设置在run.models，它被传递给run.mark.model。默认值是external=FALSE，但如果它被设置为TRUE的标志模型对象被保存在一个外部文件的扩展名.rda和与其匹配的MARK输出文件的文件名相同的基本。在工作区中的标记对象是一个字符串，是保存的图像（例如，“mark001.rda”）的文件的名称。如果external=TRUE与mark.wrapper然后产生的marklist包含一个列表条目每个标记模式，即只有文件名，然后在最后一个项目是model.table。在工作区中的所有功能识别标记对象的双重性（即，文件名或标记对象）。所以，即使标记对象仅包含文件名，功能，如print.mark或summary.mark工作。不过，如果你使用external=TRUE和不使用的功能之一，你想看看在标记对象的一部分，然后使用功能load.model。然而，您可能输入mymark$results，如果你使用的是external=TRUE，你将取代以上
Functions store and restore were created to store externally and restore models from external storage into the R workspace. They work on a marklist and are only needed to store externally existing marklist models or ones originally created with external=FALSE or to restore if you change your mind and decide to keep
功能store和restore创建store外部和restore模型从外部存储到R的工作空间。他们的工作在marklist和只需要store外部存在的marklist模型或最初创建时external=FALSE或restore，如果你改变了主意，决定继续
Error in setup for robust design occupancy models with more than 2 primary sessions was fixed. The error resulted in mark.exe crashing.
强大的设计占用模型2个以上的初级会话设置中的错误是固定的。错误导致mark.exe崩溃。
The concept of time-varying individual covariates has been expanded to include robust design models which have both primary (session) and secondary (time) occasion-specific data. For a robust design, a time-varying individual covariate can be either session-dependent or session-time dependent. As an example, if there are 3 primary sessions and each has 4 secondary occasions, then the individual covariates can be named x1,x2,x3 to be primary session-dependent or named x11,x12,x13,x14,x21,x22,x23,x24,x31,x32,x33,x34. The value of x can be any name for the covariate. In the formula only the base name is used (e.g., ~x) and RMark fills in the individual covariate names that it finds that match either the session or session-time
随时间变化的个体协变量的概念已经扩大到包括强大的设计模型，有小学（会话）和二级（时间）的场合特定的数据。对于一个强大的设计，一个随时间变化的个别的协变量可以是依赖会话或会话的时间依赖性。作为一个例子，如果有3个主会话，每个有4个二次场合，那么该个体的协变量可以名为x1，X2，X3是主会话依赖或命名x11的，×12，×13，×14，X21，X22，X23 ，X24，X31，X32，X33，X34。 x的值可以是任何名字的协变量。式中的基本名称（例如，~x）和RMark填写个人的协变量的名称，它认为那场比赛无论是在会话或会话的时间
Version 1.8.1 (19 May 2008)
版本1.8.1（2008年5月19日）
Added function summary.ch to provide summaries of the capture history data (resighting matrices and m-arrays). It will not work with all types of models at present. It will work with CJS
新增功能summary.ch提供的捕获历史数据（resighting矩阵与M阵列）的摘要。目前，它不会与所有类型的模型。将与CJS
Added argument model.name to model.table to be able to use alternate names in the model table. It can use either the model name with each mark object which uses a formula notation (the current approach) or it can use the name of the R object containing the mark model (model.name=FALSE). See model.table for an example. Also, the help file for model.table was updated to reflect the code
添加参数model.namemodel.table能够使用替代模型中的表的名称。它可以使用的型号名称与每个标记的对象，它使用一个公式符号（目前的做法），也可以使用包含标记模型（model.name=FALSE）R对象的名称。见model.table一个例子。此外，帮助文件为model.table的代码进行了更新，以反映
Code in mark.wrapper was modified to output the number of columns and column names of the design matrix for each model if run=FALSE. This allows a check of each of the columns included in the model. By reviewing these you can assess whether the model was constucted as you intended. If there is any question you can either use model.matrix or make.mark.model to examine the design
如果mark.wrapper代码run=FALSE为每个模型进行了修改，输出的设计矩阵的列名和列名。这允许包含在模型中的每个列的支票。通过审查这些，你可以评估模型是否constucted，如您所想。如果有任何问题，你可以使用model.matrix或make.mark.model检查的设计
A bug in the new function merge.design.covariates was fixed in which merge was sorting the design data which does obvious bad things. Adding sort=FALSE does not appear to mean that the data frame is left in its original order. To prevent this, the dataframe is forced to remain in its original order by adding a sequence
一个错误的新功能merge.design.covariates被固定在其中merge排序的设计数据做了明显的不好的事情。添加sort=FALSE不出现意味着数据框留在原来的顺序。为了防止这种情况，数据框被迫保持在其原来的顺序，通过添加一个序列
Version 1.8.0 (8
版本1.8.0（8
Fixed a bug in model.average that caused it to fail and issue an error when any of the models included a time dependent covariate in the parameter being averaged.
修正了一个在model.average会导致失败，并发出一个错误，当任何模型包含一个随时间变化的协变量的参数平均。
Added merge.design.covariates which is meant to replace merge.occasion.data. This new function allows covariates to be assigned by time, time and group, or just group. It also uses a simplified list of arguments and works with individual design dataframes rather than the entire ddl. It uses the R function merge which can be used on its own to merge design covariates into the design data. You can use merge directly as this function only checks for some common mistakes before it calls merge and it handles reassignemnt of row names in the case were design data have been deleted. An example, where you might want to use merge instead of this function would be situations where the design data are not just group, time or group-time specific. For example, if groups were specified by two different factor variables say initial age and region and the design covariates were only region-specific. It would be more efficient to use merge directly rather than this function which would require an entry for each group which would be each pairing of inital age and region. If you use merge and you deleted design data prior to merging, save the row.names, merge and then
加入merge.design.covariates这是为了取代merge.occasion.data。这个新功能允许，以被分配的time，time和group，或只是group的协变量。它也使用了简化的参数列表和个人的设计dataframes，而不是整个DDL的作品。它使用R函数merge可以其自身上使用合并到的设计数据的设计协变量。你可以用merge直接作为本函数只检查一些常见的错误，然后调用merge和处理reassignemnt行名称的情况下，设计数据已被删除。一个例子，在这里，你可能想使用merge，而不是这个功能是设计数据的情况下，不只是组，时间或一组特定时间。例如，如果指定的组分别由两个不同的因子变量说初始年龄和区域和设计的协变量只有特定区域。这将是更有效地使用merge，而不是直接功能，这需要一个条目，每个组，它将是各配对，初始索年龄和区域。如果你用merge，你删除的设计数据合并之前，的row.names保存，合并，然后
An argument run was added to mark.wrapper. If set to FALSE, then it will run through each set of models in model.list and try to build each model but does not attempt to run it. This is useful to check for and fix any errors in the formula before setting off a large run. If you use run=FALSE do not include arguments that are meant to be passed to
的论据run加入mark.wrapper。如果设置为FALSE，然后它会运行在model.list通过各组模型，并尝试建立每个模型，但不尝试运行它。这是非常有用的，掀起了大运行前检查并修正公式中的任何错误。如果你用run=FALSE不包括参数是要传递给
Version 1.7.9 (7 April 2008)
1.7.9版（2008年4月7日）
make.design.data was fixed so that remove.unused=T will work properly when different
make.design.data固定，使remove.unused=T工作时，不同的
Version 1.7.8 (12 March 2008)
版本1.7.8（2008年3月12日）
Changed the default link for N to log in the setup.parameters for the HetClosed and FullHet. It was incorrectly set to logit which created incorrect estimates to be computed in model.average because MARK forces the log
改变为N默认的链接登录的setup.parameters的HetClosed和FullHet。有人错误地设置为罗吉特计算model.average不正确的估计，因为MARK强制log
Version 1.7.7 (6 March 2008)
版本1.7.7（2008年3月6日）
Supressed warning message that occurred with code to check the validity of the sin link in
Supressed警告消息出现的代码来检查的有效性的罪恶链接的
Fixed a couple of bugs in covariate.predictions that prevented it from working for some cases after including
修正了几个错误的covariate.predictions，阻止它从工作后，某些情况下，包括
Added function release.gof to construct the RELEASE goodness of fit test and extract the TEST2 and TEST3
新增功能release.gof构建释放拟合优度检验，并提取TEST2和TEST3
Version 1.7.6 (26
版本1.7.6（26
make.mark.model was modified to change the capitalization of the link functions and to remove all spaces after "=" in the input file for mark.exe. These differences were preventing the MARK interface from fully importing the model. Although the model would be imported and could be run inside the MARK interface, median c-hat would not run and would give an error stating "Invalid Link" for any model imported from RMark. Now transfering a model from RMark to the MARK interface is fully functional (I hope). If you want to import an output file that was created with a prior version of RMark without re-running it, use a text editor on the output file and remove any spaces before and after an = sign. Then change the capitalization of the links to "Logit", "MLogit", "Log", "LogLog", "CLogLog",
make.mark.model修改，，改变资本化的链接功能，并删除所有“=”后面的空格中输入文件mark.exe。这些差异，防止的MARK接口从全面导入模型。虽然该模型将被导入，并可以运行里面的MARK接口，中位数C-帽子将无法运行，并会给出一个错误，说明为任何进口RMark的模型“无效的链接”。现在转让的模型，从RMark的MARK接口，是全功能的（我希望）。如果你想导入与以前版本的RMark没有重新运行它的输出文件被创建，使用文本编辑器的输出文件，并删除任何空格之前和之后的等号（=）。然后，改变资本的链接“Logit模型”，“MLogit”，“log”中，“LogLog”中，“CLogLog”，
The sin link is now supported if the formula for the parameter generates an identity matrix for the parameter. For example, if you use ~-1+time instead of ~time then the resulting design matrix will be an identity for time. Likewise, for interactions use ~-1+group:time instead of ~group*time. If you select the sin link and the resulting design matrix is not an identity for the parameter, an error will be given and
现在支持的罪链接，如果公式的参数生成一个身份矩阵的参数。例如，如果你使用~时间~（-1）+时间，而不是最终的设计矩阵将是一个身份的时间。同样，对于交互使用~（-1）+组~组的时间，而不是时间。如果您选择的罪链接和由此产生的设计矩阵的参数是不是一个身份，一个错误将给出
To match the output from MARK, the confidence intervals for real parameters using any 0-1 link including loglog,cloglog,logit and sin are now computed using the logit transformation. For previous versions this will only affect any results that were using loglog and cloglog. Previously, it was using the chosen link to compute the se and the interval endpoints. The latter is still used for the log and identity links
为了配合MARK的输出，使用任何0-1链接loglog，cloglog，Logit和罪恶的实际参数的置信区间计算的使用罗吉特转型。对于以前的版本，这只会影响使用的任何结果，loglog和cloglog。此前，有人使用所选择的链路来计算本身和的时间间隔端点。后者是用于log和身份的链接
The model "Jolly" was added to the supported list of models. Parameters include Phi,p,Lambda,N. It is not a particularly numerically stable model and often will not converge. Use of options="SIMANNEAL" in call to mark is recommended for better convergence. It will take much
“快乐”的模型被添加到支持的型号列表。这些参数包括Phi，LAMBDA，N，P这不是一个特别数值上是稳定的模型，往往不会收敛。使用选项=的“SIMANNEAL”，在调用mark建议为更好地衔接。这将需要多
Version 1.7.5
版本1.7.5
model.average was modified to ignore any models that did not run and
model.average进行了修改，忽略不运行任何模型和
read.mark.binary and extract.mark.output were modified to extract and store the real.vcv matrix (var-cov matrix of the simplified real parameters) in the mark object if realvcv=TRUE. The default is realvcv=FALSE. This argument has been added to functions mark, run.mark.model and
read.mark.binary和extract.mark.output进行了修改，以提取和存储real.vcv的基质（VAR-COV矩阵的简化实时参数）中的标记对象，如果realvcv TRUE。默认值是= FALSE realvcv。这个论点已经被添加到功能mark，run.mark.model和
An argument delete has also been added to mark and run.mark.model. The default value is FALSE but if set to TRUE it deletes all output files created by MARK after extracting the results. This is most useful for simulations that could easily create thousands of output files and after extracting the results the model objects are no longer needed. This is just a convenience
也被添加到一个论点删除mark和run.mark.model。的默认值是FALSE，但是如果设置为TRUE，它会删除所有的MARK创建的输出文件解压后的结果。这是最有用的模拟，可以很容易地创建成千上万的输出文件，解压后不再需要的对象模型的结果。这仅仅是一个方便
Version 1.7.4 (10 Jan 2008)
版本1.7.4（2008年1月10日）
A bug in make.mark.model was fixed. It was preventing creation of individual (site) covariate models for parameters with only a single parameter (single index) in certain circumstances like Psi1 in the
中的bugmake.mark.model是固定的。这是防止个人创造的（网站）PSI1的协变量的模型参数，只有一个参数（单指数）在某些情况下，如
The fix to merge.occasion.data in version 1.7.1 did not work when design data had been deleted. That has been
在版本1.7.1的修复merge.occasion.data没有工作时，设计数据已被删除。这一直是
Various functions with some operating specific calls have been modified so they will work on either Windows or Linux. Thus, the there is a single file for all source/help for both operating systems in RMarkSource.zip. It can be downloaded to either Windows or Linux to build the package. You need to build the package for Linux but not for Windows. For Windows, you only need RMark.zip which contains the pre-built package which only needs to be installed. Currently, with Linux the variable MarkPath is ignored and mark.exe is assumed to be in the path. Also, for Linux the default for MarkViewer is "pico" (an editor on some Linux machines). This can be modified in print.mark or by setting MarkViewer to a different value. The one Linux specific function is read.mark.binary.linux. The function extract.mark.output calls either read.mark.binary.linux or read.mark.binary depending on the operating system. A Linux version of mark.exe (32 or 64 bit) can be
各种功能的一些经营特定的呼叫已被修改以便它们能在Windows或Linux操作系统。因此，有一个单独的文件的所有源/帮助这两个操作系统中RMarkSource.zip。它可以下载到Windows或Linux建立的包。你需要建立包的Linux，但不适用于Windows。对于Windows，你只需要RMark.zip，其中包含预建的包，只需要安装。目前，Linux的被忽略的变量MarkPath，和mark.exe被认为是路径中的。此外，对于Linux的默认值MarkViewer是“微型”的编辑器（在某些Linux机器）。这可以修改print.mark或将MarkViewer设置为不同的值。一个Linux特有的功能是read.mark.binary.linux。函数extract.mark.output调用是read.mark.binary.linux或read.mark.binary视操作系统而定。的mark.exe的Linux版本（32位或64位）
Version 1.7.3 (4 Jan 2008)
版本1.7.3（2008年1月4日）
In working with the occupancy models, it became apparent that it would be useful to have a new function called make.time.factor which creates time-varying dummy variables from a time-varying factor variable. An example is given using observer with the occupancy dataset weta from the
在的入住模型工作，很明显，这将是非常有用的一个新的函数make.time.factor产生随时间变化的虚拟变量随时间变化的因素变量。观察员给出了一个示例使用与占用的数据集weta的
To match the results in the book, I added arguments use.AIC and use.lnl to function model.table to construct a results table with AIC rather than AICc and -2LnL values. The latter is more useful with a mix of models some using individual covariates and others not.
匹配的结果在这本书中，我添加参数use.AIC：use.lnl函数model.table来构造一个结果表AIC，而不是AICC和2LnL的值。后者是更有用的混合模式使用单独的协变量和别人不。
A modification was made to make.mark.model with the MSOccupancy model to fix the name of the added data for parameter p1 when share=TRUE to be p2. For an example which uses p2 to construct an additive model, see
一个修改，是为了make.mark.model与MSOccupancy模型的数据参数p1当share=TRUE是p2的名称来解决。举一个例子，使用P2构建添加剂模型，请参阅
Version 1.7.2 (20 Dec
版本1.7.2（12月20日
In changing code for the occupancy models, a brace was misplaced which prevented the nest survival models from working. This has been fixed. Also, the example code for mallard and killdeer was modified to exclude the calls to process the input file. This enables use of the function example() to run the example code (e.g. example(mallard)). From now on as I add examples they are being included in my test set to avoid this type
在更改代码的占用模型，大括号是没有道理的，防止巢生存模式工作。这已得到修复。此外，示例代码mallard和killdeer被修改，以排除呼叫处理输入文件。这使得使用该功能example()运行的示例代码（如：example(mallard)）。从现在开始我添加的例子，他们被包含在我的测试设置，以避免这种类型的
Version 1.7.1 (14 Dec 2007)
版本1.7.1（2007年12月14日）
If you update with this version of RMark make sure to update MARK also, so you get the fixes for
如果您在更新与RMark这个版本的确保更新MARK，所以你得到修复
A minor bug was fixed in function merge.occasion.data that created duplicate row names and prevented the design data from
被固定在了一个小错误函数merge.occasion.data创建重复的行名，避免了设计数据
Thirteen different occupancy models were added. Models in the following list use the designation from MARK: Occupancy, OccupHet, RDOccupEG, RDOccupPE, RDOccupPG, RDOccupHetEG, RDOccupHetPE, RDOccupHetPG,OccupRNPoisson, OccupRNNegBin,OccupRPoisson,OccupRNegBin,MSOccupancy. Het means it uses the Pledger mixture and those with RD are the robust design models. The 2 letter designations for the RD models are shorthand for the parameters that are estimated. For EG, Psi, Epsilon, and Gamma are estimated, for PE gamma is dropped and for PG, Epsilon is dropped. For the latter 2 models, Psi can be estimated for each primary occasion. The last 5 models include the Royle/Nichols count (RPoisson) and presence (RNPoisson) models and the multi-state occupancy model. See salamander for an example of Occupancy, OccupHet, Donovan.7 for an example of OccupRNPoisson,OccupRNNegBin, Donovan.8 for an example of OccupRPoisson,OccupRNegBin, see RDSalamander for an example of the robust design models and NicholsMSOccupancy for an example of MSOccupancy. salamander
13个不同的占用模型。从以下列表中的型号使用指定MARK：Occupancy, OccupHet, RDOccupEG, RDOccupPE, RDOccupPG, RDOccupHetEG, RDOccupHetPE, RDOccupHetPG,OccupRNPoisson，OccupRNNegBin,OccupRPoisson,OccupRNegBin,MSOccupancy。 Het是指它采用了质的混合物，那些RD强大的设计模型。的2个英文字母代号的RD模型的参数估计的缩写。 EG，PSI，ε，和Gamma估计，PE伽玛下降，PG，Epsilon是下降了。对于后者的2个型号，PSI可以估计为每所小学的场合。在过去的5款车型，包括罗伊尔/尼科尔斯数（RPoisson）和的存在（RNPoisson）模型和多占用模型。 salamander的一个例子Occupancy, OccupHet，Donovan.7的一个例子OccupRNPoisson,OccupRNNegBin，Donovan.8OccupRPoisson,OccupRNegBin，看到一个例子<X >的一个例子强大的设计模型和RDSalamander的NicholsMSOccupancy的一个例子。 MSOccupancy
The functions create.model.list and mark.wrapper were modified so that a list of parameters can be used to loop. This is useful in the situation with shared parameters such as p1 and p2 in the MSOccupancy model, closed models etc. See p1.p2.different.dot in NicholsMSOccupancy for an example. It can also be useful if the model definitions are linked conceptually (e.g., when one parameter is time dependent,
的职能create.model.list和mark.wrapper被修改，以便可以使用循环的参数列表。这是非常有用的情况下与共享参数，如p1和p2MSOccupancy模型，closed模型等。p1.p2.different.dotNicholsMSOccupancy 的一个例子。它也可以是有用的，如果链接的概念模型的定义（例如，当一个参数是时间依赖性，
The "." value in an encounter history is now acceptable to RMark and gets passed to MARK for interpretation as a missing
“。”在遭遇历史现在接受的RMark的的值被传递到标记为丢失的解释
print.marklist was fixed to show the model table properly after a c-hat adjustment was made. The change in the code in version 1.6.5 to add parameter specific values to the model table had the side-effect of dropping the model name if c-hat was
print.marklist固定表明，该模型表后正常的c帽子作出调整。 1.6.5版中的代码添加参数值的变化的模型表的副作用丢弃的型号名称，如果C-帽子
Version 1.7.0 (7 Nov 2007)
版本1.7.0 2007年（7月11日）
A function deltamethod.special for computation of delta method variances of some special functions was added. It uses the function deltamethod from the package msm. You need to install the package msm from CRAN to use it.
加入的功能deltamethod.special计算Delta的一些特殊功能的方法差异。它使用功能deltamethod从包msm。您需要安装套件“msmCRAN使用它。
A more complete example (mallard) created by Jay Rotella was added for the nest survival model. His script provides a nice tutorial for RMark and the utility of R to provide a wide-open capability to calculate/plot etc with the results. It also demonstrates the advantages of scripting in R to document your analysis and enable it to be repeated. Before you use his tutorial you need to install the package plotrix from CRAN. At a later date, Jay has said he will add some additional examples to demonstrate use of the deltamethod function to create variances for
一个更完整的例子（mallard）由杰伊·罗特拉为巢的生存模式。他的脚本提供了一个很好的教程RMark和公用事业的R提供一个开放的计算能力/图等的结果。它还演示了脚本的优势，在R记录您的分析，并使它能够被重复。在你使用他的教程之前，你需要从CRAN安装包plotrix的。在以后的日子，周杰伦表示，他将添加一些额外的例子演示如何使用deltamethod功能创造差异
Various changes were made to help files. A more complete description of cleanup was given to tie into
各种变化进行了帮助文件。更完整的说明cleanup扎入
Version 1.6.9 (10 Oct
版本1.6.9（10月10日
Nest survival model was added to list of MARK models supported by RMark. See killdeer for an example. Note that the data structure for nest models is completely different from the standard capture history so the functions import.chdata, export.chdata and convert.inp do not work with nest data structure.
鸟巢的生存模型被添加到列表的MARK模型所支持的RMark。见killdeer一个例子。需要注意的是鸟巢模型的数据结构是完全不同的标准的捕捉历史，所以功能import.chdata，export.chdata和convert.inp不与嵌套数据结构。
Slight change was made to run.mark.model and print.markto accomodate change in R 2.6.0.
轻微的改动是为了run.mark.model和print.mark，以适应变化在R 2.6.0。
Version 1.6.8 (2 Oct 2007)
版本1.6.8（2007年10月2号）
Changes were made to merge.occasion.data to enable group and time-specific design covariates to be added to the design
merge.occasion.data，使协变量被添加到设计组，具体时间设计进行了更改，
Change was made to setup.parameters to use a log-link for N in the closed-capture models. MARK forces that link for N but the change was needed for model.average which does the inverse-link computation. Note that the reported N in model.average is actually f0 (number not seen). To get the correct values for N simply add M_t+1 (unique number captured) to f0. That is the way MARK computes N. The std error and confidence interval is on f0 such that the lower ci on N will never
更改为setup.parameters使用的log链接中的N的封闭捕捉模式。 MARK链接为N而变化的力量，需要model.average的反向链接计算。请注意，所报告的Nmodel.average F0居然（数量没有看到）。为了得到正确的N值，只需添加M_t +1（捕获的唯一编号）到F0。这是MARK计算N. STD误差和置信区间是F0等，CI的N绝不会
An error was fixed in the output of model.average. When you selected a specific parameter, it was giving a UCL which was a copy from one of the models and not the UCL from the model averaging. If you didn't specify vcv=T it only showed the errant UCL and if you did specify vcv=T then it showed the correct LCL and UCL but then added the errant UCL in a column. This occurred because it was adding covariate data for the specific parameter and was shifted a column because of a change in
错误是固定的在输出的model.average。当您选择特定的参数，这是给一个UCL是一个副本的车型之一，而不是UCL模型的平均。如果你没有指定vcv=T只显示了错误的UCL，如果你没有指定vcv=T然后它显示了正确的LCL和UCL但随后在一列中添加了错误的UCL。出现这种情况，因为它被添加协变量的数据的特定参数和被转移了一列，因为发生了变化
Version 1.6.7 (7 Aug 2007)
版本1.6.7（2007年8月7日）
Changes were made in print.mark, print.summary.mark and compute.design.data to acommodate changes in V2.5.1 of R. When upgrading versions of R problems may occur if RMark was built with an earlier version of R. The version of R that was used to build RMark is listed on the screen each time it is loaded with library(RMark) This is RMark 1.6.7 Built: R 2.5.1;
进行了更改，在print.mark，print.summary.mark和compute.design.data，以至于不能容纳R. V2.5.1的变化，当升级版本的R问题可能发生，如果RMark建与早期版本的R.每次被加载与图书馆（RMark）<CODE>的，这是RMark 1.6.7内置：R 2.5.1版本的R，用于构建RMark的是在屏幕上列出;
The help file for import.chdata was expanded to clarify the differences between it and convert.inp and the use of the freq
帮助文件import.chdata之间的差异和convert.inp和freq的使用扩大到澄清
Version 1.6.6 (14 May 2007)
版本1.6.6（2007年5月14日）
Function make.mark.model was fixed so that the real label indices were properly written when
功能make.mark.model真正的标签指数是固定的，以便正确地写入时
Function make.mark.model was also changed to remove the parameter simplification for mlogit parameters that was added in v1.4.5. I mistakenly assumed that the mlogit parameters were setup such that the normalization to sum to 1 was done will all the real parameters in the set (i.e., all PSI for a single stratum). In fact, the mlogit values are only specified for the unique real parameters so if there is any simplification and the sum of the probabilities is close to 1 (excluding subtraction value) the values will not be properly constrained. For example, with the mstrata data if the problem was constrained such that PSI from AtoB was equal to AtoC, it is still necessary to have these as separate real parameters and constrain them with the design matrix. As it turns out, with the mstrata example it does not matter because the problem is such that the sum of Psi for AtoB and AtoC is not close to 1 (same for other strata) and any link will work. This change will only be noticeable in situations in which the constraint matters (i.e., the probability for the subtraction parameter is near 0). The change back to non-simplification for mlogit parameters may increase execution times because the design matrix size has been increased. Previous users of the Multistrata design will see very little difference in there results if they only used models containing stratum:tostratum because that will create an all-different PIM within each mlogit set. When I ran the mstrata examples with this version and compared them to v1.6.5 the results were different but they were differences in the 5th or smaller decimal
函数make.mark.model也改变了删除参数简化为mlogit参数中添加了v1.4.5。我错误地认为，mlogit参数设置的标准化等于1是将所有的实际参数的集合（即一个单一的阶层，所有PSI）。事实上，mlogit值只指定独特的实际参数，因此，如果有任何的简化和概率的总和是接近1（不包括减法值）的值，将无法正确地约束。例如，如果问题是与mstrata数据约束使得PSI从ATOB等于ATOC，它仍然是需要有这些作为单独的实际参数，并约束它们的设计矩阵。事实证明，mstrata例如不要紧，因为这个问题是这样的总和的PSI ATOB和ATOC的是不关闭1（同其他阶层），任何一个环节工作。这种变化将是明显的情况下，其中的限制事项（即，减法运算参数的概率是接近0）。变回非简化mlogit参数设计矩阵的大小可能会增加执行时间，因为已增加。以前的多层次设计的用户会看到结果，如果他们只用了模型层：tostratum，因为这将创建一个不同的PIM在每个mlogit设置的非常小的差异。当我跑mstrata的例子与此版本相比，他们v1.6.5的结果是不同的，但他们在第5或更小的十进制数的差异
Version 1.6.5 ( 3 May 2007)
1.6.5版（2007年5月3日）
Function model.table was modified to include parameter formula fields in the model.table dataframe of a marklist. Previously only the model.name was included which is a concatenation of the individual parameter formulas. The additional fields allows extracting the model table results based on one of the parameter formulas or to create a matrix of model AICc or other values with rows as one parameter and colums as the other. See model.table for
函数model.table进行了修改，包括参数化方案领域的model.table数据框的marklist。以前只有model.name被列入这是一个串联的各个参数公式。额外的字段允许提取模型表的结果的基础上的参数公式之一，或创建一个矩阵的行作为一个参数和作为其他colums模型AICC或其他值。见model.table
Function process.data was modified such that factor variables used for grouping retain the ordering of the factor levels in the data file. Previously they would revert back to default ordering and the re-leveling would also have to be
功能process.data被修改，例如，用于分组保留的顺序的数据文件中的因子水平的因子变量。在此之前，他们将恢复为默认排序，再平层也必须是
An argument brief was added to mark to control
一种论调brief加入mark控制
Fixed a bug in get.real that prevented computation for
修正了一个错误的get.real，防止计算
Added code to make.mark.model that prevents constructing models with empty rows in the design matrix unless the parameter is fixed. For example, if you were to try ~-1+Time for the dipper data, it will fail now because there is no value for the intercept (Time=0).
添加的代码make.mark.model，防止构建模型的设计矩阵的空行，除非参数是固定的。例如，如果你要尝试~（-1）+时间的瓢数据的，它会失败，因为现在是没有价值的截距（时间= 0）。
Function mark.wrapper outputs the model name to the screen before running the model which helps associate any error messages to the model if
功能mark.wrapper输出到屏幕上的型号名称，然后再运行的模式，可以帮助任何错误消息关联的模型，如果
Version 1.6.4 (7 March 2007)
版本1.6.4（2007年3月7日）
A new function export.model was created to copy the output files into the naming convention needed to append them into a MARK .dbf/.fpt database so they can be used with the MARK interface features. This is useful to be able to use some of the features not contained in RMark such as median c-hat and variance component estimation. To create a MARK database, first use export.chdata to create a .inp file to pass the data into MARK. Start MARK and use File/New to create a new database. Select the appropriate Data Type (model in RMark) and fill in the appropriate values for encounter occasions etc. For the Encounter Histories File Name, select the file you created with export.chdata. Once you have created the database in the Program MARK interface, click on the Browse menu item and then Output/Append and select the output file(s) (i.e those with a Y.tmp) that you exported with export.model. Note that this will not work with output files run with versions of RMark prior to this one because the MARK interface will give a parse error for the design matrix. To get around that you can edit the output file and remove the spaces in the line with the design matrix header. For example, it should look as follows design matrix constraints=7 covariates=7 without spaces around the =
在创建一个新的函数export.model复制的输出文件的命名约定，需要把它们添加到一个MARK .dbf / .fpt的数据库，以便他们可以使用的MARK接口功能。这是非常有用的，能够使用一些如中位数C-帽子和方差分量估计不包含在RMark中的功能。要创建一个数据库标记，第一次使用export.chdata创建一个。inp文件将数据传递到MARK。开始标记和使用文件/新建“创建一个新的数据库。选择适当的数据类型（模型中RMark），并填写适当的值相遇的场合等。遭遇历史文件名，选择创建的文件与export.chdata。一旦你已经创建了数据库的程序MARK接口，点击“浏览”菜单项，然后输出/附加选择输出文件（S）（即一个Y.tmp）中导出与export.model。请注意，这将无法正常工作运行的输出文件与之前版本的RMark这一个，因为MARK接口的设计矩阵解析错误。要解决这个问题，您可以编辑输出文件，并删除空间的设计矩阵的行头。例如，它应该如下所示design matrix constraints=7 covariates=7没有空格周围=
The minor change described above was made in the input file with spacing on the design matrix line to enable proper appending of the output into a MARK
上述输入文件中的与设计矩阵行间距的微小的变化，使适当的输出追加到一个MARK
The function cleanup was modified to delete all mark*.tmp files. Do not use cleanup until you
的功能cleanup修改，删除所有标记*。tmp文件。不使用cleanup，直到你的
An argument use.comments was added to import.chdata to enable comment fields to be used as row names in the data frame. A comment is indicated as in MARK with /* comment */. They can be anywhere in the record but they must be unique and they
一个参数use.comments加入import.chdata，使注释字段被用来作为数据框中的行名。 MARK / *注释* /注释表示。他们可以随时随地的记录，但他们必须是唯一的，他们
Function create.model.list was modified such that it only includes lists with a formula element. This prevents collecting other objects that are named
功能create.model.list修改，例如，它仅包括与一个formula元素的列表。这可防止收集的其他对象被命名为
Version 1.6.3
版本1.6.3
A minor change in make.mark.model and find.covariates was made to accommodate use of the same covariate in different formulas (e.g. Phi and p). Previous code worked except any call to get.real would fail. Previously a duplicate of the covariate was entered in the data file to MARK.
一个微小的变化make.mark.model和find.covariates是相同的协变量在不同的公式（如披P），以适应使用。以前的代码工作，但不调用get.real会失败。以前的协变量的重复输入数据文件中的标记。
An argument default has been added to the model definition (parameters in make.mark.model and model.parameters in mark). The argument sets the default value for parameters
参数default已经被添加到模型定义（parametersmake.mark.model和model.parametersmark）。参数设置参数的默认值
Checks were added in make.mark.model to fail if any of the individual covariates used are either factor variables or contain NAs. Both could fail in the MARK.EXE run but the error message would be less obvious. Factor variables can work as an individual covariate, if the levels are numeric. But it was easier to exclude all factor variables from being individual covariates. They can easily be converted to a continuous version (e.g. Blackduck$BirdAge=as.numeric(Blackduck$BirdAge)-1). The code for the Blackduck was changed to make BirdAge a continuous rather than factor variable. Factor variables can still be used to define groups and then used in the formula. They just can't be used as individual covariates. This change was made because a factor variable was in the data but not defined in groups and when it was used in the formula it would create a float error in MARK.EXE and that would be
检查中添加make.mark.model失败，如果任何个人的协变量使用的任一因子变量或包含来港定居。双方可能会失败在MARK.EXE运行，但不太明显的错误消息。因子变量可以作为一个单独的协变量，如果是数字的水平。但是，这是比较容易排除所有的因素是个人的协变量的变量。他们可以很容易地转换成一个连续的版本（例如布莱克达克和$ BirdAge = as.numeric（布莱克达克$ BirdAge）-1）。代码的Blackduck进行调整，以便BirdAge一个连续的，而不是可变因素。因子变量仍然可以被用来定义组，然后在公式中使用。他们只是不能用来作为个人的变量。这种变化是因为一个因素变量的数据，但没有定义groups在公式中使用时，它会创建一个的持股量在MARK.EXE错误，这将是
Version 1.6.2 (28 Feb
版本1.6.2（2月28日
The fix in 1.6.1 to avoid the incorrect design matrix was not sufficiently general and created a parse error in R if you attempted to use any design data covariates that were created with a cut function to create factor variables by binning a
1.6.1，以避免不正确的设计矩阵中的修复不够一般，创造了一个解析错误，如果您试图使用任何设计数据创建的切割功能的协变量因子变量的分级一个在R
The code in read.mark.binary has been changed to skip over the v-c matrix for the derived parameters if it is not found in the file. This was
read.mark.binary的代码已更改为跳过了VC矩阵派生的参数，如果它没有在文件中找到。这是
Version
版本
An important bug was fixed in make.mark.model in which an incorrect design matrix would be created if you used two individual covariates in the same formula whereby one of the covariate names was contained within the other. For example, if you used ~mass+mass2 where mass2=mass^2, it would actually create a design matrix with columns mass product(mass,mass2) which would be the model mass+mass^3. This happened due to the way the code identified columns where it needed to replace dummy values with individual covariate names. Since mass was contained in mass2 it added mass to the column as a product. The code now does
一个重要的错误是固定在make.mark.model在一个不正确的设计矩阵将被创建在其中一个的协变量名，在其他相同的公式，如果你使用了两个独立的协变量。例如，如果你使用~质量+ mass2 mass2 =质量^ 2，实际上，它会创建一个设计矩阵列质量的产品（质量，mass2），这将是模型质量+质量^ 3。这发生由于代码的方式确定了与个人的协变量的名称，它需要更换虚值的列。由于质量载mass2附加质量作为一个产品的列。现在的代码做
An argument indices was added to the function model.average which enables restricting the model averaging to a specific set of parameters as identified by the all-different parameter indices. This is most useful in large models with many different indices such that memory limitations are encountered in constructing the variance-covariance matrix of the real parameters. For example, with a CJS analysis of data with 18 groups and 26 years of data, the number of parameter indices exceeds 22,000. Even by restricting the parameters to either Phi or p with the parameter argument there are still 11,000 which would attempt to create a matrix containing 11,000 x 11,000 elements which can exceed the memory limit. In most cases, there are far fewer unique parameters and this argument allows you to select which parameters to
的论据indices加入的功能model.average这使限制的模型，平均一组特定的参数所确定的所有不同的参数指标。这是最有用的大型模型有许多不同的指标，例如内存的限制，在建设中遇到的实际参数方差 - 协方差矩阵。与CJS与18个组和26年的数据的数据分析，例如，参数指数的数量超过22000。即使通过限制披或Pparameter参数的参数仍然有11000将尝试创建一个矩阵包含11000 x 11000元素可能会超过内存限制。在大多数情况下，有少得多的唯一参数，该参数允许您选择的参数
Time-varying covariates are no longer needed for all times if the formula is correctly written to exclude them in the resulting design matrix. make.mark.model still reports missing time-varying covariates but will continue to try and fit the model but if the missing variables are used in the design matrix the model will fail. As an example consider a time varying covariate x for recapture times 1990 to 1995. The code expects to find variables x1990, x1991, x1992, x1993, x1994, x1995. However, lets say that the values are only known for 1993-1995. If you define a variable I'll call recap in the design data which has a value 1 for 1993-1995 and a value 0 for 1990-1992 then if you use the formula ~recap:x the resulting design matrix will only use the known variables for 1993-1995 but you will still be warned that the other values (x1990 -
随时间变化的协变量不再需要的所有时间，如果公式是正确的写入，将其排除在最终的设计矩阵。 make.mark.model报告失踪时间变化的协变量，但将继续尝试和适合的模型，但如果缺少变量用于设计矩阵，该模型将失败。作为一个例子考虑一个随时间变化的协变量x为夺回倍1990~1995年。的代码，希望能够找到变量x1990，x1991，x1992，x1993，x1994，x1995且。然而，可以说是唯一已知的1993-1995年的值。我会打检测给在设计回顾一下1993-1995年值1和值0为1990年至1992年的数据，如果您使用的配方~回顾：如果你定义一个变量x的设计矩阵只使用已知的变量为1993年至1995年，但你还是会警告说，其他值（x1990 -
A bug was fixed in extract.mark.output which prevented it from obtaining more than the last mean covariate value from
修正了在extract.mark.output防止它获得更多的协变量的值平均比去年
fill.covariates was modified such that only a partial list of covariate values need to be specified with data and the remainder are filled in with default values depending on
fill.covariates修改，只列出了部分协变量值需要指定data，其余的默认值取决于填写
The output from summary.mark was modified for real parameters when se=T to include all.diff.index to provide the indices of each real parameter in the all-different PIM structure. They are useful to restrict covariate.predictions and model.average to a specific set of real
输出summary.mark真正的参数修改时se=T，包括all.diff.index提供的每一个真实的参数指标，在不同的PIM结构。他们是有用的限制covariate.predictions和model.average一组特定的真正
A new function covariate.predictions was created to compute real parameter values for multiple covariate values and their variance-covariance matrix. It will also model average those values if a marklist is passed to the function. Two examples from chapter 12 of Cooch and White are provided to give examples of models with individual
在创建一个新的函数covariate.predictions多因素值和它们的方差 - 协方差矩阵计算实际的参数值。它也将型号平均这些值，如果marklist传递给函数的。 COOCH和白色“第12章的两个例子是提供给个别模型的例子
The default value of vcv in model.average has been changed to
vcvmodel.average已改为默认值
Version 1.6.0 (27 Nov 2006)
版本1.6.0（2006年11月27号）
A bug was fixed in PIMS which
修正了在PIMS
Bugs were fixed in make.design.data which prevented use of argument remove.unused=T with Multistrata models and also for any type of model when
错误被固定在make.design.data防止使用参数remove.unused=TMultistrata模型，也适用于任何类型的模型时，
Bugs were fixed in process.data which gave incorrect ordering of intial ages if the factor variable for the age group was numeric and more than two digits. Also, the number of groups in the data was not correct if the number of loss on capture records exceeded the number
错误固定在process.data了不正确的顺序INTIAL年龄因素变量的年龄组数字和两个以上的数字。此外，数组的数据是不正确的，如果在采集记录的损失超过数数
Bugs were fixed in setup.parameters and setup.model that prevented use of the Barker model and that reported an erroneous list of model
错误被固定在setup.parameters和setup.model，阻止利用巴克模型和报告一个错误的模型列表
Version 1.5.9 (26 June 2006)
版本1.5.9（2006年6月26日）
A bug was fixed in convert.inp which prevented the code from working with groups and two or more covariates. Note that there are limitations to this function which may require some minor editing of the file. The limitations have been added to the help file
修正了在convert.inp防止工作组和两个或两个以上的协变量的代码。请注意，有此功能，这可能需要一些小的编辑的文件的限制。的局限性已被添加到帮助文件
Version 1.5.8 (22 June
版本1.5.8（22月6日
Argument options was added to mark and make.mark.model with a default NULL value. It is simply a character string that is tacked onto the Proc Estimate statement for the MARK .inp file. It can be used to request options such as NoStandDM (to not standardize the design matrix) or SIMANNEAL (to request use of the simulated annealing optimization method) or any existing or new options that can be set on the estimate proc.
参数optionsmark和make.mark.model默认的NULL值。这是一个简单的字符的字符串，该字符串附加到Proc Estimate语句的标志。inp文件。它可用于请求的选项如NoStandDM（不规范设计矩阵）或SIMANNEAL（请求使用的模拟退火优化方法）或任何现有的或新的选项，可以设置上的估计进程内。
A bug in model.table was fixed so it would accomodate the change from v1.3 to a marklist in which the model.table was switched to the last entry in
中的bugmodel.table是固定的，所以它会适应的变化从V1.3到marklist的，的model.table切换到的最后一个项目
A bug in summary.mark was fixed so it would properly display QAICc when chat > 1.
中的bugsummary.mark是固定的，所以它会正确地显示QAICc的聊天> 1时。
Function adjust.chat was modified such that it returns a marklist with each model having a new chat value and the model.table is adjusted for the
功能adjust.chat被修改，每个模型有一个新的聊天值和model.table，它返回一个marklist调整为
Function adjust.parameter.count was modfied so it returns the mark model object rather than using eval to modify the object in place. The latter does not work with models in a marklist and calls made within
modfied功能adjust.parameter.count所以它返回的标记模型对象，而不是使用eval修改该对象的地方。后者不工作在marklist的模型，并调用内作出
Version 1.5.7 (8 June 2006)
版本1.5.7（于二零零六年六月八日）
Argument data was added to function model.average to enable model averaging parameters at specific covariate values rather than the mean value of the observed data. An example is given in
参数data加入运作model.average，使模型平均参数的观测数据的平均值，而不是在特定的协变量值。给出一个例子在
Argument parameter of function model.average now has a default of NULL and if it is not specified then all of the real parameters are model averaged rather than those for a
参数parameter功能的model.average现在有一个默认值为NULL，如果没有指定，那么所有的实际参数模型的平均值，而不是那些为
A bug was fixed in function compute.real that caused the function to fail for computations of
一个错误是固定的在函数compute.real导致函数失败的计算的
Version 1.5.6 (6 June 2006)
版本1.5.6（2006年6月6日）
print.summary.mark was modified so fixed
print.summary.mark修改，以便固定
Argument show.fixed was added to summary.mark to control whether fixed parameters are shown as NA (FALSE) or as the value at which they were fixed. If se=T the default is show.fixed=T otherwise show.fixed=F. The latter is most useful in displaying values in PIM format (without std errors), so
参数show.fixedsummary.mark固定的参数来控制是否显示为NA（FALSE）或在它们被固定的值。如果se=T默认的是show.fixed=T否则show.fixed=F。后者是最有用的显示值，在PIM格式（无标配错误），因此
Argument links was added to convert.link.to.real and the default value for argument model is now NULL. One or the other must be given. If the value for links is given then they are used in place of the links specified in the model object. This provides for additional flexibility in changing link values for computation (eg
参数linksconvert.link.to.real和参数model的默认值是现在NULL。一方或另一方必须提供。如果links的值给出，那么它们被用来代替在model对象指定了该书。这提供了额外的灵活性，改变链路计算的值（例如：
Argument drop was added to model.average. If drop=TRUE (the default), then any model with one or more non-positive (0 or negative) variances is not
参数drop加入model.average。如果drop=TRUE（默认值），然后与一个或多个非正（0或负）的方差的任何模型是不
An error in computation of the v-c matrix of mlogit link values in compute.links.from.reals was fixed. This did not affect confidence intervals for real parameters (eg Psi) in model.average because it uses the logit transformation for confidence intervals on real
VC矩阵mlogit链接值计算中的错误compute.links.from.reals是固定的。这并不会影响实际参数的置信区间（如PSI），在model.average，因为它使用的Logit真正转变为置信区间
get.real was unable to extract a single parameter value(eg constant Phi model). This was fixed.
get.real是无法提取单个参数值（如恒定披模型的）。这是固定的。
The argument parm.indices was removed from the functions compute.real and convert.link.to.real because the subsetting can be done easily with the complete results returned by the functions. This changed the examples in
从功能的参数parm.indices compute.real和convert.link.to.real可以很容易做到，因为子集的完整函数返回的结果。这改变中的示例
compute.real and subsequently get.real return a field fixed when se=TRUE that denotes whether a real parameter is a fixed parameter or an estimated parameter at a boundary which
compute.real“，随后get.real返回一个字段fixedSE = TRUE，表示实际参数是否是一个固定的参数或参数估计在边界
Version
版本
model has been deleted from the arguments in TransitionMatrix. It was only being used to ascertain whether the model was a Multistrata model. This is now determined more accurately by looking for the presence of tostratum in the argument x which is a dataframe created for Psi from the function get.real. The function also works with the estimates dataframe generated from model.average. See help for
model已被删除，从参数中TransitionMatrix。它只是被用来确定模型是否是一个多层次的模型。现在这是通过寻找的存在下，更准确地确定tostratum在参数中x是Psi从函数get.real创建的数据框。该功能也可以的估计数据框产生的model.average。请参阅帮助信息
An argument vcv was added to function model.average. If the argument is TRUE (the default value) then the var-cov matrix of the model averaged real parameters is computed and returned and the confidence intervals for the model averaged parameters are constructed. Models with non-positive variances for betas are reported and dropped from model averaging and the weights are renormalized for the remaining models.
的论据vcv被添加到功能model.average。如果参数为TRUE（默认值），然后计算VAR-CoV的矩阵模型的平均实际参数，并返回和模型的置信区间的平均参数的构造。模型报告和模型平均下降差异贝他非正的权重，归一化剩余的模型。
A new function compute.links.from.reals was added to the library to transform real parameters to its link space. It has 2 functions both related to model averaged estimates. Firstly, it is used to transform model averaged estimates so the normal confidence interval can be constructed on the link values and then back-transformed to real space. The second function is to enable parametric bootstrapping in which the error distbution is assumed to be multivariate normal for the link values. From a single model, the link values are easily constructed from the betas and design matrix so this function is not needed. But for model averaging there is no equivalent because the real parameters are averaged over a variety of models with the same real parameter structure but differing design structures. This function allows for link values and their var-cov matrix to be created from the model averaged real
一个新的函数compute.links.from.reals添加到库中的链接，空间转换实际参数。它有2个功能相关的平均估计模型。首先，它是用来变换模型所以正常的置信区间可以构造上的链接值，然后再转化为实际空间中的平均估计。第二个功能是，使该错误distbution被假定为多元常态为链接值的参数的自举。从一个单一的模式，很容易链接值的测试版和设计矩阵的构造，所以这个功能是不需要的。但是，对于模型的平均是不相等的，因为真正的参数的平均值多种型号相同的参数结构，但不同的设计结构。此功能允许链接值和它们的变种冠状病毒的矩阵，可以从模型中创建的平均实际
Version 1.5.4 (30 May 2006)
版本1.5.4（2006年5月30日）
In function mark an argument retry was added to enable the analysis to be re-run up to the number of times specified. An analysis is only re-run if there are "singular" beta parameters which means that they are either non-estimable (confounded) or they are at a boundary. Beginning with this version, extract.mark.output was modified such that the singular parameters identified by MARK are extracted from the output (if any) and the indices for the beta parameters are stored in the list element model$results$singular. The default value for retry is 0 which means it will not retry. When the model is re-run the initial values are set to the values at the completion of the last run except for the "singular" parameters which are set to 0. Using retry will not help if the parameters are non-estimable. However, if the parameters are at a boundary because the optimization "converged" to a sub-optimal set of parameters, then setting retry to 1 or a suitably small value will often help it find the MLEs by moving away from the boundary. If the parameters are estimable and setting retry does not work, then it may be better to set new initial parameters by either specifying their values or using a
在功能mark参数retry加入，使分析重新运行指定的次数。只有重新运行分析，如果有“奇异”的测试参数，这意味着他们要么不难能可贵（混淆），或他们是在边界。从这个版本开始，extract.mark.output修改，从输出中提取的奇异参数识别MARK（如果有的话）和指标的测试参数都存储在列表中的元素model$results$singular。 retry的默认值是0，这意味着它不会重试。当模型被重新运行的初始值被设置为在完成最后一次运行除了“奇异的”参数被设置为0的值。使用retry不会帮助如果参数不难能可贵的。但是，如果参数的边界，因为优化“融合”的一个次优的参数设置，然后设置retry1或适当的小值往往会远离，帮助它找到的最大似然估计边界。如果参数是难能可贵的，设置为retry不工作，那么它可能是更好的新的初始参数设置通过指定属性值，或者使用
A new function rerun.mark was created to simplify the process of refitting models with new starting values when the models were initially created with mark.wrapper which runs a list of models by using all combinations of the formulas defined for the various parameters in the model. Thus, individual calls to mark are not constructed by the user and re-running an analysis from the resulting list would require constructing those calls. The argument model.parameters is now stored in the model object and it is used by this new function to avoid constructing calls to rerun the analysis. With this new function you only need to specify the model list element to be refitted, the processed dataframe, the design data and the model list element (or different model) to be used for initial values. See rerun.mark for an
在创建一个新的函数rerun.mark简化改装模型的过程中，新的起点值当模特们最初创建的mark.wrapper运行使用的所有组合的公式定义的各种型号列表在模型中的参数。因此，个人检测mark不构成并重新运行分析，从结果列表中的用户将需要兴建这些调用。参数model.parameters现在存储模型中的对象，它是由这个新的功能，以避免建设的要求重新运行分析。有了这个新的功能，你只需要指定模型列表中的元素进行改装，处理后的数据框，设计数据和模型列表中的元素（或不同的模型）用于初始值。见rerun.mark为
To make rerun.mark a viable approach for all circumstances, the functions mark.wrapper and model.table were modified such that models that fail to converge at the outset (i.e., does not provide estimates in the output file) are stored in the model list created by the former function and they are reported as models that did not run and are skipped in the model.table by the latter function. This enables a failed model to be reanalyzed with rerun.mark using another model that
为了使rerun.mark所有情况下的可行办法，功能mark.wrapper和model.table修改，例如，在一开始就无法收敛的模型（即不提供估计在输出文件中）都存储在模型中创建的列表的前一个函数和模型，没有运行，后者的功能被跳过的model.table的报告。这使得rerun.mark使用另一种模式，一个失败的模式被重新定义
Version 1.5.3 (25 May
版本1.5.3（5月25日
In function get.real a fix was made to accommodate constant pims and a warning is given if the v-c matrix for the betas has non-positive
在功能get.real一个修正，以适应不断PIMS，并发出警告，如果VC矩阵的测试版非正
In function make.mark.model, the argument initial can now be a single value which is then assigned as the initial value for all betas. I have found this useful for POPAN models. For some models I have run, the models fail to converge in MARK with the default initial values it uses (I believe it uses initial=0). I have had better luck using initial=1. By allowing the use of a single value you can use the same generic starting value for each model without figuring out the number of betas in each model. Also note that you can specify another model that has already been run to use as initial values for a new
在功能make.mark.model，initial参数现在可以是一个单值，然后将其分配为初始值的所有测试版。 POPAN模型，我发现这是非常有用的。我所遇到的一些模型，该模型无法收敛MARK的默认初始值（我相信它使用了initial=0）。我有更好的运气使用initial=1的。通过允许使用一个单一的值，可以使用相同的通用的为每个模型的初始值没有搞清楚的数目在每个模型中的测试版。另外请注意，你也可以指定其他模式，已经运行到一个新的使用作为初始值
A bad bug was fixed in cleanup which was unfortunately deleting files containing "out", "inp", "res" or "vcv" rather than those having these as extensions. This happened without your knowledge if you chose ask=FALSE. Good thing I had a backup. Anyhow, I have now restricted it to files that are named by RMark with markxxxx.inp etc where xxxx is a numeric value. Thus if you assign your own basefile name for output files you'll have to delete them manually. Better safe
cleanup不幸被删除“走出去”，“INP”，“水库”或“VCV”，而不是那些具有这些扩展名的文件，其中包含一个坏的错误是固定的。在您不知情的情况下发生的，如果你选择问= FALSE。好东西，我有一个备份。无论如何，我现在已经限制了它的文件被命名为由RMark与markxxxx.inp等，其中xxxx是一个数值，。因此，如果你分配自己的BASEFILE的输出文件的名称，你就必须手动删除它们。更好的安全
Version 1.5.2 (18 May 2006)
版本1.5.2（二零零六年五月十八日）
Two new functions were added in this version. convert.inp converts a MARK encounter history input file to an RMark dataframe. This will be particularly useful for those folks who have already been using MARK. Instead of converting and importing their data with import.chdata they can use the convert.inp to import their .inp file directly. It can also be used to directly import any of the example .inp files that accompany MARK and the MARK electronic book (http://www.phidot.org/software/mark/docs/book/). The second new function is only useful for tutorials and for first time users trying to understand the way RMark works. The function PIMS displays the full PIM structure or the simplified PIM structure for a parameter in a model. The user does not directly manipulate PIMS in RMark and they are essentially transparent to the user but for those with MARK experience being able to look at the PIMS may help with
在这个版本中增加了两个新的功能。 convert.inp转换为MARK遭遇历史上输入的文件到一个RMark的数据框。这将是特别有用的那些人已经在使用MARK。而不是他们的数据转换和导入import.chdata，“他们可以使用convert.inp直接导入他们的inp文件。它也可以被用于直接导入任何的例子。INP文件陪MARK和对MARK电子的书（http://www.phidot.org/software/mark/docs/book/）。第二个新功能是有用的教程和用户第一次试图理解的方式RMark的作品。函数PIMS显示完整的PIM结构的简化PIM结构模型中的参数。用户不直接操作PIMS在RMark，他们本质上是对用户透明的，但对于那些能看的PIMS MARK经验可以帮助
Version 1.5.1 (11 May 2006)
版本1.5.1（二零零六年五月十一日）
Functions compute.link and get.link were added to compute link values
功能compute.link和get.link加入到计算链接值
A function convert.link.to.real was added to convert link estimates to real parameter estimates. Previously a similar internal function was used within compute.real but to provide more flexibility it
的功能convert.link.to.real添加到转换链路估计的实际参数估计。此前一个类似的内部功能内使用compute.real“可是，提供更多的灵活性，
An argument beta was added to get.real to enable it to be changed in the computation of the real parameters rather than always using the values in
的论据betaget.real，使其能够真正的参数计算，而不是始终使用中的值改变
A function TransitionMatrix was added to create a transition matrix for the Psi values. It is provided for all strata including the subtract.stratum. Standard errors and confidence intervals can also be
的功能TransitionMatrix添加到创建的PSI值的转换矩阵。它提供各阶层包括subtract.stratum。也可以是标准误差和置信区间
make.mark.model was modified to include time.intervals as an element
make.mark.model进行了修改，包括time.intervals元素
Version 1.5.0 (9 May 2006)
版本1.5.0（二零零六年五月九日）
If output file already exists user is given option to create mark model from existing files. Only really useful if a bug occurs (which occurred to me from 1.4.9 changes) and once fixed any models already run can be brought into R by running the same model over and specifying the existing base filename. Base filename values are no longer prefixed with MRK to
如果输出文件已经存在，用户给定的选项，从现有文件创建标记模型。只有真正有用的，如果出现一个错误（1.4.9的变化发生在我身上），一旦固定任何机型已经运行，可以带入R的运行相同的模型，并指定现有的基础filename。碱基filename值不再前缀，MRK
On occasion MARK will complete the analysis but fail to create the v-c matrix and v-c file. The code has been modified to skip over the file
有时MARK将完成分析，但无法创建VC矩阵和VC文件。代码已被修改，跳过的文件
Two new functions have been added to ease handling of marklist objects. merge.mark merges an unspecified number of marklist and mark model objects into a new marklist with an optional model.table. remove.mark can be used to remove mark models from a marklist. See dipper for
两个新的功能已被添加以缓解处理marklist对象。 merge.mark合并数目不详的marklist和标记的模型对象与一个可选的model.table到一个新marklist的。 remove.mark可用于，删除标记从marklist模型。见dipper
Various changes were made to functions that compute real parameter estimates, their standard errors, confidence intervals and variance-covariance matrix. The functions that were changed include compute.real,find.covariates,get.real,fill.covariates.
各种变化进行了计算的实际参数估计，其标准误差，置信区间和方差 - 协方差矩阵的功能。被改变的功能，包括compute.real，find.covariates，get.real，fill.covariates。
Version 1.4.9 (3 May 2006)
版本1.4.9（二零零六年五月三日）
Argument initial of make.mark.model was not working after model simplification was added in v1.2. This was modified to select initial values from the model based on names of design matrix columns rather than column contents which have different numbers of rows
参数initialmake.mark.model没有工作模型简化后加入1.2版。这被修改，以从模型中选择的初始值，根据设计矩阵列的名称而不是列的内容有不同的行数
extract.mark.output was fixed to extract the correct -2LnL from the output file in situations in
extract.mark.output是固定的提取正确的2LnL的情况下，在输出文件中
Version 1.4.8 (25
版本1.4.8（25
Argument silent was added to mark and mark.wrapper with a default value of FALSE. This overcomes the problem described above
参数silent加入mark和mark.wrapper的默认值FALSE。这克服了上面所述的问题
Code was added to collect.model.names to prevent it from tripping up when files contain an asterisk which R uses
添加代码collect.model.names防止绊倒了文件包含R使用一个星号
Use of T and F was properly changed to TRUE and FALSE in various functions to prevent
的T和F正确的使用各种功能，以防止TRUE和FALSE
Code for naming files was modified to avoid problems when more than 999
命名文件的代码被修改，以避免出现问题时，超过999个
Bug in setting fixed parameters with argument
问题设置固定的参数与参数
Argument remove.intercept was added to parameter definition to force removal of intercept in designs with nested factor interactions with additional factor variables (e.g., Psi=list(formula=~sex+stratum:tostratum,remove.intercept=TRUE)).
参数remove.intercept加入参数定义，，强制清除拦截的设计与嵌套因素的相互作用与其他因素变量（例如，Psi=list(formula=~sex+stratum:tostratum,remove.intercept=TRUE)）。
Version 1.4.7 (10 April 2006)
版本1.4.7（二零零六年四月十日）
An error was fixed in the Psi simplification code. Note that with the fix in 1.4.2 to trap errors, a side effect is that non-trapped errors that occur in the R code will now fail without any error messages. If the error occurs in making the model, then the model will not be run, but you will not receive a message that the model failed. I may have to make the error trapping a user-settable
固定在了一个错误的Psi简化代码。需要注意的是1.4.2中的修复来捕获错误，一个副作用是，非陷发生的错误，在R代码将失败，没有任何错误消息。如果发生错误的模型，该模型将不能运行，但你不会收到一条消息，该模型失败。我可能有错误捕获一个用户可设置
Version 1.4.6
版本1.4.6
Assurance code was added to test that the mlogits were properly assigned. An error message will be given if there has been any unforeseen problem created by the simplification. This eliminates any need for the user to check them as
保证代码添加到测试的mlogits正确分配。将得到一个错误信息，如果有任何不可预见的问题简化。这消除了任何需要用户检查它们作为
Version 1.4.5 (6 April
版本1.4.5（4月6日
For multistrata models, the code for creating the mlogit links for Psi was not working properly if there was more than one group. This was
对于多层次模型，psi的创建mlogit链接的代码是不正常工作，如果有一个以上的组。这是
Simplification of the PIMS has now been extended to include mlogit parameters. That was not a trivial exercise and while I feel confident it is correct, double check the assignment of mlogit links for complex models, as I have not checked many examples at present. Within a stratum, the corresponding elements for Psi for each of the tostratum (movement from stratum to each of the other strata excluding the subtract.stratum) should have the same mlogit(xxx) value such that it can properly compute the value for
简化的PIMS现在已经扩展到包括mlogit参数。这不是一项简单的工作，而我深信它是正确的，仔细检查的分配复杂的模型mlogit链接，因为我没有检查过很多例子。地层内的，相应的元件为每个的tostratum帕普西（运动从分层的每个其他阶层不包括的subtract.stratum）应该具有相同mlogit，（xxx）的值，使得能够正确地计算的值
Version 1.4.4
版本1.4.4
By including the test on model failure, errors that would stop program were not being displayed. This has been fixed in this version.
包括测试模型失效，会停止程序的错误，并没有被显示出来。在此版本中已修正此问题。
An error was fixed in using time-varying covariates
错误是固定的使用时间变化的协变量
Version
版本
Problem with pop up window has been fixed. It will no longer appear if the model does not converge but the model will show as having
弹出窗口的问题已得到修复。它将不再出现，如果模型不收敛，但该模型将显示为有
An error was fixed in extracting output from the MARK output file when for some circumstances the label for beta parameters included spaces. This now
错误已修正中提取某些情况下，从的MARK输出文件时，输出的标签测试参数包括空格。现在这
Version 1.4.2 (14 March 2006)
版本1.4.2（2006年3月14号）
Errors in the FORTRAN code were preventing completion of large batch jobs. Now these errors are caught and models that fail are reported and skipped over. Unfortunately, it does require user intervention to close the popup window. Make sure you select Yes to close the window especially if you use the default invisible=FALSE such that the window does not appear. If you select No, you will not able to close the
FORTRAN代码中的错误，防止大批量作业的完成。现在，这些错误被发现和失败的模型，报告和跳过。不幸的是，它不需要用户干预，以关闭弹出窗口。确保你选择“是”关闭该窗口，特别是如果你使用默认的invisible=FALSE的窗口不会出现。如果你选择“否”，您将无法关闭
A new list element was added to parameters in make.design.data for parameters such as Psi to set the value of tostratum that is computed by subtraction. The default is to compute the probabilitity of remaining in the stratum. The following is an example with strata A to D and setting A to be computed by subtraction for each stratum: <br> ddl=make.design.data(data.processed, <br> parameters=list(Psi=list(pim.type="constant",subtract.stratum=c("A","A","A","A")), <br> p=list(pim.type="constant"),S=list(pim.type="constant")))
一个新的列表元素添加到parametersmake.design.data等参数的Psitostratum设置的值的计算方法是减法。默认情况下是计算的probabilitity，地层中的剩余。下面是一个例子阶层A到D和A的计算减法各阶层：参考DDL make.design.data（data.processed，<BR>参考P =（pim.type =“不变”），S =列表（pim.type =“不变”）））
Version 1.4.1 (11 March 2006)
版本1.4.1（2006年3月11日）
A value "constant" was added for the argument pim.type. Note that pim.type is only used for triangular
值“不变”的说法pim.type。请注意，pim.type仅用于三角
Some code changes were made to make.mark.model which lessen time to create the MARK input file for large
一些代码进行了更改，make.mark.model减少的时间来创建MARK输入文件大
Function add.design.data was modified to accomodate robust design and deletion of
功能add.design.data进行了修改，以适应强大的设计和删除
model.name argument in mark and make.mark.model was not working. This was
model.namemark和make.mark.model不工作参数。这是
Version 1.4 (9 March 2006)
版本1.4（2006年3月9日）
Robust design models added. See robust for
强大的设计模型。见robust
Function cleanup was modified so warning messages/errors do not occur if no
功能cleanup修改，以便警告消息/错误不会发生，如果没有
Parameters in the design matrix are now ordered in the same consistent arrangement. In prior versions they were arranged based
在设计矩阵的参数现在订购相同一致的安排。在以前的版本中，他们被设
Argument right was added to make.design.data, add.design.data and in design.parameters of make.mark.model to control whether bins are inclusive on the right (default). The robust example uses this
参数rightmake.design.data，add.design.data中design.parametersmake.mark.model控制箱是否包括在右边（默认）。 robust的示例使用此
Version 1.3
1.3版
Time varying covariates can now be included in the model formula. See
现在可以随时间变化的协变量包括在模型公式。看
New model types for Known (Known-fate) and Multistrata (CJS with different strata) were added. See Blackduck and mstrata for
已知的（已知的命运）和多层次（CJS让不同阶层）增加了新的模型类型。见Blackduck和mstrata
Specific rows of the design data can now be removed for parameters that should not be estimated. Default fixed values can be assigned. The function make.design.data now accepts an argument remove.unused which can be used to automatically remove unused design data for nested models. It's behavior is also determined by the new argument default.fixed in make.mark.model.
现在可以移除的设计数据的具体行不应该被估计的参数。可以分配默认的固定值。该功能make.design.data现在接受一个参数，remove.unused这可用于自动删除未使用的嵌套模型的设计数据。它的行为也取决于新的参数default.fixedmake.mark.model。
summary.mark now produces a summary object and print.summary.mark prints the summary object. Changes were made to output when
summary.mark现在的总结性对象和print.summary.mark打印的汇总对象。进行了更改输出时
A new function merge.occasion.data was created to add occasion
是创建一个新的函数merge.occasion.data添加场合
New functions mark.wrapper and create.model.list were created to automate running models from a set of model specifications for
的新功能mark.wrapper和create.model.list自动运行模型的建立是为了从一组型号规格
The argument begin.time in process.data can now be a vector to enable a different beginning time for each
参数begin.time中process.data现在可以是一个向量，使一个不同的开始时间为每
An argument pim.type was added to parameter specification to enable using pims with time structure for data sets with a single release cohort for
一个参数pim.type加入参数规格也能使用PIMS随着时间的数据结构设置一个版本队列
Model lists created with collect.models are now given the class "marklist" which is used with cleanup and print.marklist
产品型号列表创建collect.models现在类的“marklist”使用cleanup和print.marklist，
The function collect.models now places the model.table at the end of the returned list such that each model number in model.table is now the element number in the
该函数collect.models现在将model.table的结束时返回的列表，例如，每个型号在model.table是现在的元素中的号码
Input, output, v-c and residual results files from MARK are now stored in the directory containing the .Rdata workspace. They are numbered consecutively and the field output contains the base filename. The function cleanup was created to delete files that are no longer linked to mark or
输入，输出，VC和剩余的结果文件MARK现在都存储在该目录中包含.Rdata工作区。他们的编号连续领域output的包含基本文件名。函数cleanup的建立是为了不再mark或删除文件
Model averaged estimates and standard errors of real parameters can be obtained
模型的平均的估计，可以得到实参数的标准误差
Version
版本
By default the PIM structure is simplified to use the fewest number of unique parameters. This reduces the size of the design
默认情况下，PIM的结构得到简化，使用最少数量的唯一参数。这减少了尺寸的设计
The above change was made in some versions still numbered 1.1, but it contained an error that caused the links command for
上述变化是在某些版本编号为1.1，但它包含一个错误，导致链接“命令
adjust argument has been added to collect.models to enable control of number of parameters and resulting
adjust参数已加入collect.models，使控制参数的数量以及由此产生的
model.list in model.table and adjust.chat can now also be a list of models created by collect.models which allows operating on
model.list在model.table和adjust.chat现在也被允许经营上的列表创建的模型collect.models
（作者）----------Author(s)----------
Jeff Laake
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发表于 2012-9-26 23:49:13
