rbind.capthist(secr)
rbind.capthist()所属R语言包：secr
Combine capthist Objects
结合capthist对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Form a single capthist object from two or more compatible capthist objects.
从两个或多个兼容capthist对象，形成一个单一的capthist对象。
用法----------Usage----------
MS.capthist(...)
rbind.capthist(..., renumber = TRUE, pool = NULL, verify = TRUE)
参数----------Arguments----------
参数：...
one or more capthist objects or lists of capthist objects
一个或多个capthistcapthist对象的对象或列表
参数：renumber
logical, if TRUE assigns new composite individual ID
逻辑，如果是TRUE分配新的复合个人ID
参数：pool
list of vectors of session indices or names
向量的会话指数或名称列表
参数：verify
logical, if TRUE the output is checked with verify
逻辑，如果为true，输出检查verify
Details
详细信息----------Details----------
MS.capthist concatenates the sessions in the input objects as one multi-session capthist object. Each session may use a different detector array (traps) and a different number of sampling occasions. Session names are derived implicitly from the inputs, or may be given explicitly (see Examples); if any name is duplicated, all will be replaced with sequential integers. The ... argument may include lists of single-session capthist objects.
MS.capthist连接会话输入对象，作为一个多届capthist对象。每个会话可能会使用不同的探测器阵列（陷阱）和不同数量的采样场合。会话名称是从输入端隐式，或者可以被显式给出的（见实施例），如果任何名称被复制，所有将被替换为连续整数。该...参数可能包括列表的单日capthist对象。
rbind.capthist is used to pool capture data from more than one session into a single session. The number of rows in the output session is the sum of the number of rows in the input sessions (i.e. each animal appears in only one session).
rbind.capthist用于从多个会话池捕获的数据到一个单一的会话。输出会话中的行数是输入会话中的行数（即每个动物出现在只有一个会话）的总和。
For rbind.capthist, the ... argument may be
对于rbind.capthist，在...参数可以是
A series of single-session capthist objects, which are pooled to form one new single-session object, or
一系列的单日capthist对象，都被集中起来，形成一个新的单会话对象，或
One multi-session capthist object, when the components of "pool" are used to define combinations of old sessions; e.g. pool = list(A=1:3, B=4:5) produces an object with two sessions (named "A" and "B") from 5 old ones. If pool = NULL (the default) then all the sessions are pooled to form one single-session capthist object.
一个多届capthist对象时，使用“池”的组成部分的旧会话定义的组合; pool = list(A=1:3, B=4:5)生成一个对象（命名为A和B），从5岁的两会。如果pool = NULL（默认值），那么所有的会议都被集中起来，形成一个单一的会话capthist对象。
Sessions to be pooled must have the same number of capture occasions and use the same detectors (traps). At present there is no function to pool data from different detector arrays.
以集中的会话必须具有相同数量的捕获场合，并使用相同的检测器（陷阱）。目前还没有功能从不同的探测器阵列存储池数据。
The names of arguments other than ... should be given in full. If renumber = TRUE (the default), the session name will be prepended to the animal ID before pooling: animals 1, 2 and 3 in Session A will become A.1, A.2 and A.3, while those in Session B become B.1, B.2 and B.3. This ensures that each animal has a unique ID. If renumber = FALSE, the animal IDs will not change.
参数以外的名称...应给予充分。如果renumber = TRUE（默认值），会话名称将被追加到前池：动物1，第2和第3会议将成为A.1，A.2，A.3的动物ID，而那些在会话B B.1，B.2和B.3。这确保了每个动物都有一个唯一的ID。如果renumber = FALSE，动物ID将不会改变。
Other attributes (xy, signal) are handled appropriately. If the signal threshold (attribute "cutval") differs among sessions, the maximum is used and detections of lower signal strength are discarded.
的其他属性（XY，信号）得到正确处理。如果信号的阈值（属性“cutval”）不同的会话之间，最大的使用和丢弃检测到的信号强度较低。
The use of rbind.capthist to concatenate sessions is now deprecated: use MS.capthist.
使用rbind.capthist来连接会话现在已经过时：使用MS.capthist。
Although MS.capthist and rbind.capthist look like S3 methods, they aren't. The full function names must be used.
虽然MS.capthist和rbind.capthist看起来像S3的方法，他们是不。完整的函数的名称必须使用。
值----------Value----------
For MS.capthist, a multi-session object of class "capthist" with number of sessions equal to the number of sessions in the objects in ....
对于MS.capthist，多会话对象的会话的会话中的对象的数量相等数量的类的capthist“......
For rbind.capthist, either an object of class "capthist" with one session formed by pooling the sessions in the input objects, or a capthist object with more than one session, each formed by pooling groups of sessions defined by the "pool" argument. Covariate columns that appear in all input sessions are retained in the output.
对于rbind.capthist，要么是对象的类capthist与一个形成在输入对象汇集会话的会话，或capthist对象与多个会话，每个汇集由定义的会话组形成池“的说法。协方差的列中出现的所有输入会话保留在输出中。
参见----------See Also----------
capthist, subset.capthist
capthist，subset.capthist
实例----------Examples----------
## extend a multi-session object[＃延长一个多会话对象]
## we fake the 2010 data by copying from 2005[＃假冒的2010年的数据复制从2005年]
## note how we name the appended session[＃注意我们是如何命名的附加会话]
fakeCH <- ovenCH[["2005"]]
MS.capthist(ovenCH, "2010" = fakeCH)
## simulate sessions for 2-part mixture[＃模拟会话两部分组成的混合物]
temptrap <- make.grid(nx = 8, ny = 8)
temp1 <- sim.capthist(temptrap,
detectpar = list(g0 = 0.1, sigma = 40))
temp2 <- sim.capthist(temptrap,
detectpar = list(g0 = 0.2, sigma = 20))
## concatenate sessions[＃串联会话功能]
temp3 <- MS.capthist(large.range = temp1, small.range = temp2)
summary(temp3)
## session-specific movement statistic[＃会话特定的运动统计]
RPSV(temp3)
## pool sessions[＃池中会议的]
temp4 <- rbind.capthist(temp1, temp2)
summary(temp4)
RPSV(temp4)
## compare mixture to sum of components[＃比较混合物分量总和]
## note `detectors visited' is not additive for 'multi' detector[＃注意探测器访问“是不是多探测器添加剂]
## nor is `detectors used'[＃也不是探测器采用“]
(summary(temp1)$counts + summary(temp2)$counts) -
summary(temp4)$counts
## Not run: [＃不运行：]
## compare two different model fits [＃比较两个不同的模型拟合]
tempfit3 <- secr.fit(temp3, CL = T, buffer = 150, model = list
(g0 ~ session, sigma ~ session), trace = FALSE)
predict(tempfit3)
## if we can tell which animals had large ranges...[＃如果我们可以知道哪些动物有大范围...]
covariates(temp4) <- data.frame(range.size = rep(c("large",
"small"), c(nrow(temp1), nrow(temp2))))
tempfit4 <- secr.fit(temp4, CL = T, buffer = 150, model = list
(g0 ~ range.size, sigma ~ range.size), trace = FALSE)
predict(tempfit4, newdata = data.frame(range.size = c("large",
"small")))
## End(Not run)[＃（不执行）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
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发表于 2012-9-30 00:02:25
