yourcast(YourCast)
yourcast()所属R语言包：YourCast
Time-series cross-sectional Forecasting
时间系列剖预测
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Runs a set of regression models to forecast time-series cross-sectional data by either considering independent regressions in each cross-sectional unit or by
运行一组回归模型预测时间序列横截面数据，无论是考虑每个横截面的单位或独立的回归
用法----------Usage----------
yourcast(formula=NULL, dataobj=NULL,sample.frame=c(1950,2000,2001,2030),
standardize=TRUE, elim.collinear=FALSE,
tol=0.9999, solve.tol = 1.e-10,svdtol=10^(-10),
userfile=NULL, savetmp = T, model.frame=FALSE,
debug = F, rerun= "yourcast.savetmp",
### specific to models
model="OLS",zero.mean=FALSE,
#### smooth over ages
Ha.sigma = 0.3,
Ha.sigma.sd= 0.1, Ha.deriv=c(0,0,1),
Ha.age.weight=0, Ha.time.weight=0,
#### smooth over time
Ht.sigma= 0.3,
Ht.sigma.sd=0.1, Ht.deriv=c(0,0,1),
Ht.age.weight=0, Ht.time.weight=0,
#### smooth over age-time
Hat.sigma=0.2,
Hat.sigma.sd=0.1,Hat.a.deriv=c(0,1),Hat.t.deriv=c(0,1),
Hat.age.weight=0,Hat.time.weight=0,
#### smooth over cntry-time
Hct.sigma=0.3, Hct.sigma.sd =0.1,
Hct.t.deriv=1, Hct.time.weight = 0,
LI.sigma.mean=0.2,LI.sigma.sd = 0.1, nsample= 500,
low.pow=T, verbose=TRUE)
参数----------Arguments----------
参数：formula
A standard R formula of the form y \sim x_1 + x_2, except that an explanatory variable is included for a particular cross-section only if it is both listed in the formula and available in that cross-section's data set (see dataobj). Explanatory variables in the formula but not available for a cross-section (or in a cross-sectional dataset but not in the formula) are excluded. (For mortality forecasting, the specification looks like log(deaths/population) \sim x_1 + x_2, with deaths and population stored as separate variables in each dataframe.) (May be set to NULL if savetmp was set to TRUE on the last run, in which case the value of formula will come from the saved file.)
甲标准R公式的形式y \sim x_1 + x_2，不同的是只有当它是两个中所列的公式和在该横截面的数据集提供，包括为一个特定的横截面的说明变量（见dataobj ）。在式的解释变量，但没有可用的横截面（或在一个横截面的数据集，但不是在式）被排除在外。 （死亡率预测，规格看起来像log（死亡数/人口） \sim x_1 + x_2的，死亡和人口存储作为单独的变量中的每一个数据框。）（可设置为NULL如果savetmp TRUE的最后运行的，在这种情况下，该值的公式会从已保存的文件。）
参数：dataobj
A object of class "yourcast" or equivalent. See help(yourprep) for more details. The dataobj may be supplied in one of four ways. Most commonly, the argument will specify (1) an object (in working memory) or (2) a string with the name of a file in the working directory. However, if (3) dataobj is a string referring to a directory on disk, then each element of the list above should be stored in a file in that directory, with element "data" consisting of a subdirectory containing separate ASCII data files. (If this option is chosen, a complete data object, called "dataobj.Rdata", will be stored in the directory named, and it will be loaded automatically if yourcast is run again with this chosen option.) (4) The last option is for dataobj to be set to NULL, after which the function will look for a "yourcast.savetmp" file in the working directory from a previous run of the function where the argument savetmp was set to TRUE. The function yourprep is available to help construct the dataobj in the proper format from individual cross section files in the working directory or the workspace. This function also performs a number of diagnostics to ensure that the data is entered properly and can be read by yourcast. See help(yourprep) for more information
一个对象类的yourcast或同等学历。见help(yourprep)更多详情。 dataobj可以提供以下四种方式之一。最常见的是，该参数将指定（1）一个对象（工作记忆）或（2）在工作目录中的文件的名称的字符串。但是，如果（3）dataobj的是一个字符串元素的数据组成的一个子目录中有单独的磁盘上的目录，然后在该目录中的文件存储在上面的列表中的每个元素， ASCII数据文件。 （如果选择此选项，一个完整的数据对象，被称为“dataobj.Rdata，将被保存在指定的目录，它会被自动加载yourcast如果再次运行这个选择的选项。）（4）最后一个选项是将其设置为dataobj NULL，之后，该功能将寻找一个yourcast.savetmp文件在工作目录中的功能从以前的运行参数savetmp设置为TRUE。函数yourprep是可以帮助建设dataobj从各个截面的工作目录或工作区中的文件以正确的格式。此功能也执行许多诊断，以确保数据被正确输入，并且可以读取由yourcast。 help(yourprep)的详细信息见
参数：sample.frame
Vector. A four element vector containing, in order, the start and end time periods to be used for the observed data and the start and end time periods to be forecast. Years identified here that are not available for a cross-section are ignored. Default: c(1950,2000,2001,2030).
向量。甲4个元素的向量，包含，开始和结束时间的期间中，为了将用于所观察到的数据，以预测期间的开始和结束时间。此确定的年份是不可用的横截面被忽略。默认值：c(1950,2000,2001,2030)。
参数：standardize
Boolean. Should the covariates in each cross-sectional unit be standardized (to zero mean and standard deviation of 1)? Standardization is performed for both the in- and out-of-sample periods. Default: TRUE.
布尔值。应在每个横截面的单位的协变量进行标准化（零均值和标准偏差为1）？在和out-of-取样周期进行标准化。默认值：TRUE。
参数：elim.collinear
Boolean. Whether collinearity among covariates should be tested and those that are collinear shoul be eliminated. Default: FALSE.
布尔值。无论是共线之间的协变量进行测试和那些线的shoul被淘汰。默认值：FALSE。
参数：tol
Double scalar. Tolerance to find collinearities among covariates. Default: 0.9999.
双标量。耐collinearities之间的协变量。默认值：0.9999。
参数：solve.tol
A real number smaller than one that is used in the argument of the R-function solve to invert matrices (see description for tol). Default: 1^{-10}.
一个实数小于1的参数中使用的R-函数solve反转矩阵（tol详见）。默认值：1^{-10}。
参数：svdtol
A scalar; the tolerance used in inverting a matrix by SVD. Default: 10^{-10}.
标量的耐受性反转矩阵的SVD。默认值：10^{-10}。
参数：userfile
A string with the name of a file that contains your values for some or all of yourcast's arguments. This file contains R code that changes default values of arguments. E.g., the file might contain: <PRE> index.code <- 30 data <- "WHOmortalityData" </PRE> If an option is specified in userfile, it takes precidence over command line options, so it is normally best to specify each option in either the userfile or the command line but not both. Default: NULL
一个字符串，其中包含您的部分或全部yourcasts参数值的文件的名称。该文件包含的R代码更改的参数的默认值。例如，文件中可能包含的<PRE> index.code - 30数据 - “WHOmortalityData”</ pre>如果一个选项中指定userfile，它需要通过命令行选项的优先选项，所以它通常是最好的userfile或命令行中指定每个选项，但不能同时。默认值：NULL
参数：savetmp
If TRUE, yourcast saves a file in the default directory (called "yourcast.savetmp") with preliminary calculations. If the value of formula or dataobj is missing when yourcast is called, yourcast will get their values from this file, if it exists. This saves a minute or so of computing time for large data sets and is useful for multiple runs on the same data with different formulas specified or different prior values. If FALSE, no file is saved. (The structure of "yourcast.savetmp" is for the convenience of yourcast and is not intended to be read by the user or saved for more than one run.) Default: TRUE.
如果TRUE，yourcast的文件保存在默认目录（称为yourcast.savetmp）的初步计算。如果formula或dataobjyourcast被称为，yourcast会得到他们的价值观从这个文件，如果存在的话缺少的价值。这样可以节省一分钟左右，对于大数据的计算时间设置多个指定不同的公式或不同以前的值相同的数据上运行是非常有用的。如果FALSE，没有文件被保存。 （结构的“yourcast.savetmp是yourcast不打算由用户读取或保存多个运行）。默认的便利，：TRUE的。
参数：model.frame
If TRUE, include entire input dataobj in the output object. Default: FALSE.
如果TRUE，包括整个输入dataobj的输出对象。默认值：FALSE。
参数：debug
Boolean. It puts the environment that contains parameters and arguments of the simulation in the user workspace. Default FALSE.
布尔值。它把环境，其中包含的参数和变量的模拟用户工作区中。默认FALSE。
参数：rerun
String. The name of the file that is saved in the default directory with preliminary calculations; see savetmp. Default: yourcast.savetmp
字符串。名的文件保存在默认目录中的初步计算; savetmp。默认值：yourcast.savetmp
参数：model
A string indicating the forecasting method, including: Bayes maximum a posteriori (map), Bayes with Gibbs sampling (bayes), Ordinary Least Squares (ols), Poisson (poisson), and Lee-Carter (LC). Default: ols. (We usually recommend map.) yourcast also includes a procedure to help users set the sigma parameters below automatically for the case of model=map, and smoothing over age, time, or age and time, but for only one country. You may do this by running a preprocessing instance of yourcast first by setting this parameter to ebayes and using either the data to be analyzed or a larger data set which is likely to have similar or related parameter values. When ebayes is chosen, the yourcast output object will contain only the parameter values to feed into the next run of yourcast.
一个字符串，指示的预测方法，包括：贝叶斯最大后验概率（map），与Gibbs抽样的贝叶斯（bayes），普通最小二乘法（ols），泊松（poisson ）和李 - 卡特（LC）。默认值：ols。 （我们通常建议map。）yourcast的还包括一个程序，帮助用户设定的标准差以下参数的情况下，模型自动=map，平滑岁以上，时间，或年龄和时间，但只有一个国家。你可以这样做，通过设置这个参数来yourcast和使用的数据进行分析或更大的数据集可能有类似或相关的参数值，通过运行一个预处理实例ebayes第一。当ebayes选择，yourcast输出对象将只包含参数值喂到下一次运行的yourcast。
参数：zero.mean
A boolean or named vector with a value of \barμ for each age group. If TRUE, the prior has zero mean. If FALSE, the prior has nonzero mean centered around the observed mean age profile (i.e., the average of Y over time and levels of the geographic index for each age group). Default: FALSE.
一个布尔值，命名为向量的 \barμ各年龄组的值。如果TRUE，之前具有零均值。如果FALSE，之前有非零意味着，围绕观测到的平均年龄分布（即平均Y随着时间的推移和水平的GEO指标，各年龄组）。默认值：FALSE。
参数：Ha.sigma
This can be set in one of three ways: (1) a scalar which sets σ_a, the prior standard deviation of E(Y), indicating how much to smooth E(Y) over age groups (which may vary over geographic areas and time periods, and with the standard deviations averaged over age groups). A larger standard deviation represents more prior uncertainty, which allows the data to play a greater role. (2) NA to not smooth in this way. (3) To have yourcast search for a good value based on a target value of the derivative of E(Y) with respect to age, set to a vector of elements containing the start and end of a range in sigma in which to look (such as 0.05 and 1.5), the number of values to look at within this range (such as 5), and the target value of the derivative of E(Y) with respect to age (such as 0.05). The vector may also include a fifth element, which is the target value of the total standard deviation of E(Y) over all dimensions of the prior (such as 0.1). (You may choose to run yourcast with model=ebayes on a related data set to find an approximate target value of the derivative and standard deviation automatically.) Default: 0.30.
这可以设置以下三种方式之一：（1）一个标量，它设置 σ_a， E(Y)，多少顺利 E(Y)的岁以上组（先前的标准差可能会随GEO区域和时间段，并与标准偏差的平均值超过年龄组）。一个较大的标准偏差表示更前的不确定性，使数据发挥更大的作用。 （2）NA不顺畅是这样的。 （3）有yourcast搜索 E(Y)，设置为相对于年龄sigma中含有的范围的开始和结束的一个向量的元素的衍生物的目标值的基础上的一个很好的价值在其中寻找（如0.05和1.5），看的值的数目（例如5），在该范围内和所述目标值的衍生物 E(Y)相对于年龄（如0.05） 。该向量还可以包括的第五元素，它是总E(Y)对所有尺寸的现有（如0.1）的标准偏差的目标值。 （您可以选择运行yourcast的模型=ebayes找出一个大致的目标价值的衍生工具及标准差自动设置相关的数据。）默认：0.30。
参数：Ha.sigma.sd
A scalar; the standard deviation of parameter Ha.sigma (for Gibbs sampling only). Default: 0.1.
标量的标准偏差的：参数Ha.sigma（只Gibbs抽样）。默认值：0.1。
参数：Ha.deriv
A numeric vector, each element of which is n,the degree of a (discrete) derivative of the smoothness functional with respect to the age group. Element k of this vector refers to the (k-1)th derivative, where 0 excludes the derviative, 1 includes it, and values in between include the derivative but weight it down proportionally. The first element of the vector corresponds to the weight on the derivative with respect to age of order 0 (the identity operator), the second to the weight on the derivative of order 1 (the 1st derivative), etc. For example, c(0, 1, 1) corresponds to a mixed functional that penalizes the first and second derivatives equally. The higher the order of derivative, the more local smoothness over age groups; and lowest specified derivative controls the form of prior indifference. Default: c(0, 0, 1), which usually works well.
一个数值向量，它的每个元素是n，衍生工具的平滑功能的年龄组（离散）的程度。元素k这是指(k-1)阶导数，其中0不包括derviative的矢量，它包含，和值之间，包括衍生工具，但重量比例。该矢量的第一个元素对应的衍生物上的重量相对于0阶（恒等算子），所述第二的重量上的衍生物中的1阶（一阶导数），等。例如角（年龄0，1，1）对应的混合功能，惩罚同样的第一和第二的衍生物。较高的衍生物的顺序，越是本地的平滑度以上年龄组和最低指定的衍生工具控制之前，冷漠的形式。默认值：的c(0, 0, 1)，通常效果很好。
参数：Ha.age.weight
A scalar or a numeric vector with weights that determine how much smoothing occurs for different age groups. If set to 0 or NA, age groups are weighted equally; if set to a nonzero scalar, the weight for age group a is set proportional to a^Ha.age.weight; if a vector of length A, the ath element is the weight of age group a. Default: 0.
一个标量或数字向量的权重，确定如何为不同年龄组别的发生平滑。如果设置为0或NA，年龄组平均加权，如果设置为一个非零的标量，重量岁年龄组的aa^Ha.age.weight;如果一个向量的长度为A，<成正比X>个元素的权重年龄组 a。默认值： a。
参数：Ha.time.weight
A scalar or a numeric vector with weights that determine how much smoothing occurs for different time periods when smoothing over age groups. If 0 or NA, time periods are weighted equally; if set to a nonzero scalar value, the weight for time period t in smoothing age groups is proportional to t^Ha.time.weight; if the argument is a vector of length T, the tth element is the weight of time period t. Default: 0.
一个标量或数字向量的权重，确定有多少不同的时间段时，发生平滑平滑岁以上组。如果0或NA，权重相等的时间段，如果设置为一个非零的标值，时间段的权重 t平滑年龄组中的比例，以t^Ha.time.weight;如果该参数是一个向量，长度为T，t个元素的权重的时间内t。默认值：0。
参数：Ht.sigma
This can be set in one of three ways: (1) a scalar which sets σ_t, the prior standard deviation of E(Y), indicating how much to smooth E(Y) over time periods (which may vary over geographic areas and age groups, and with the standard deviations averaged over time periods). A larger standard deviation represents more prior uncertainty, which allows the data to play a greater role. (2) NA to not smooth in this way. (3) To have yourcast search for a good value based on a target value of the derivative of E(Y) with respect to time, set to a vector of elements containing the start and end of a range in sigma in which to look (such as 0.05 and 1.5), the number of values to look at within this range (such as 5), and the target value of the derivative of E(Y) with respect to time (such as 0.05). The vector may also include a fifth element, which is the target value of the total standard deviation of E(Y) over all dimensions of the prior (such as 0.1). (You may choose to run yourcast with model=ebayes on a related data set to find an approximate target value of the derivative and standard deviation automatically.) Default: 0.30.
可以设置以下三种方式之一：（1）一个标量，它设置 σ_t，先前的标准差E(Y)，说明平滑多少E(Y)“”随着时间的推移期间（可能会随GEO区域和年龄组，并与标准偏差的平均值随时间期间）。一个较大的标准偏差表示更前的不确定性，使数据发挥更大的作用。 （2）不适用不顺畅是这样的。 （3）有yourcast搜索 E(Y)相对于时间，设置为sigma中含有的范围的开始和结束的一个向量的元素的衍生物的目标值良好的值的基础上的在其中寻找（如0.05和1.5），在该范围内（例如5），和所述目标值的衍生物 E(Y)的值的数目来看看相对于时间（如0.05） 。该向量还可以包括的第五元素，它是总 E(Y)对所有尺寸的现有（如0.1）的标准偏差的目标值。 （您可以选择运行yourcast的模型=ebayes找出一个大致的目标价值的衍生工具及标准差自动设置相关的数据。）默认：0.30。
参数：Ht.sigma.sd
A scalar; the standard deviation of parameter Ht.sigma (for Gibbs sampling only). Default: 0.1.
标量参数Ht.sigma（只Gibbs抽样）的标准偏差。默认值：0.1。
参数：Ht.deriv
A numeric vector, each element of which is n, the degree of a (discrete) derivative of the smoothness functional with respect to time. Element k of this vector refers to the (k-1)th derivative, where 0 excludes the derviative, 1 includes it, and values in between include the derivative but weight it down proportionally. The first element of the vector corresponds to the weight on the derivative with respect to time of order 0 (the identity operator), the second to the weight on the derivative of order 1 (the 1st derivative), etc. For example, c(0, 1, 1) corresponds to a mixed functional that penalizes the first and second derivatives equally. The higher the order of derivative, the more local smoothness over time; and lowest specified derivative controls the form of prior indifference. Default: c(0, 0, 1), which usually works well.
一个数值向量，它的每个元素是n，相对于时间的平滑功能（离散）衍生的程度。元素k这是指(k-1)阶导数，其中0不包括derviative的矢量，它包含，和值之间，包括衍生工具，但重量比例。第一个元素的矢量对应的衍生金融工具的重量相对于时间的顺序0的身份（运营商），第二个1阶导数（一阶导数），重量等。例如，c(0, 1, 1)对应惩罚同样的第一和第二的衍生物的混合功能。较高的顺序衍生随着时间的推移，更多的本地平滑，最低指定的衍生工具控制之前，冷漠的形式。默认值：的c(0, 0, 1)，通常效果很好。
参数：Ht.age.weight
A scalar or a numeric vector with weights that determine how much smoothing occurs for different age groups when smoothing over time. If set to 0 or NA, age groups are weighted equally in smoothing over time; if set to a nonzero scalar, the weight for age group a is set proportional to a^Ht.age.weight; if a vector of length A, the ath element is the weight of age group a. Default: 0.
一个标量或数字向量的权重，确定要达到的平滑随着时间的推移发生时，为不同年龄组别平滑。如果设置为0或NA，年龄组的平均加权平滑随着时间的推移，如果设置为一个非零的标量，重量岁年龄组的aa^Ht.age.weight比例设置，如果一个向量的长度为A，ath元素的权重年龄组a。默认值：0。
参数：Ht.time.weight
A scalar or a numeric vector with weights that determine how much smoothing occurs for different time periods when smoothing over time. If 0 or NA, time periods are weighted equally; if set to a nonzero scalar value, the weight for time period t in smoothing time periods is proportional to t^Ht.time.weight; if the argument is a vector of length T, the tth element is the weight of time period t. Default: 0.
一个标量或数字向量的权重，确定有多少不同的时间段时，发生平滑平滑随着时间的推移。如果0或NA，权重相等的时间段，如果设置为一个非零的标值，时间段的权重t平滑时间段是成正比的t^Ht.time.weight;如果该参数是一个向量，长度为T，t个元素的权重的时间内t。默认值：0。
参数：Hat.sigma
This can be set in one of three ways: (1) a scalar which sets σ_{at}, the prior standard deviation of E(Y), indicating how much to smooth the time trend in E(Y) over age groups. A larger standard deviation represents more prior uncertainty, which allows the data to play a greater role. (2) NA to not smooth in this way. (3) To have yourcast search for a good value based on a target value of the derivative of E(Y) with respect to age and time, set to a vector of elements containing the start and end of a range in sigma in which to look (such as 0.05 and 1.5), the number of values to look at within this range (such as 5), and the target value of the derivative of E(Y) with respect to age and time (such as 0.05). The vector may also include a fifth element, which is the target value of the total standard deviation of E(Y) over all dimensions of the prior (such as 0.1). (You may choose to run yourcast with model=ebayes on a related data set to find an approximate target value of the derivative and standard deviation automatically.) Default: 0.2.
这可以设置以下三种方式之一：（1）一个标量，其中载 σ_{at}标准差，前E(Y)，多少时间趋势平滑E(Y)岁以上组。一个较大的标准偏差表示更前的不确定性，使数据发挥更大的作用。 （2）不适用不顺畅是这样的。 （3）有yourcast搜索良好的值的目标值的衍生物的基于E(Y)相对于年龄和时间，设置为一个向量的元素，含有的范围的开始和结束的在其中寻找在Σ（如0.05和1.5）的值的数目，在此范围内的（例如5），和所述目标值的衍生物 E(Y)相对于年龄和时间（如0.05）。该向量还可以包括的第五元素，它是总E(Y)对所有尺寸的现有（如0.1）的标准偏差的目标值。 （您可以选择运行yourcast的模型=ebayes找出一个大致的目标价值的衍生工具及标准差自动设置相关的数据。）默认：0.2。
参数：Hat.sigma.sd
A scalar; the standard deviation of parameter Hat.sigma (for Gibbs sampling only). Default: 0.1.
标量参数Hat.sigma（只Gibbs抽样）的标准偏差。默认值：0.1。
参数：Hat.a.deriv
A numeric vector, each element of which is n, the degree of a (discrete) derivative of the smoothness functional of time trends with respect to age groups. Element k of this vector refers to the (k-1)th derivative of the time trend v with respect to age, where 0 excludes the derviative, 1 includes it, and values in between include the derivative but weight it down proportionally. The first element of the vector corresponds to the weight on the derivative of the time trend with respect to age of order 0 (the identity operator), the second to the weight on the derivative of order 1 (the 1st derivative), etc. For example, c(0, 1, 1) corresponds to a mixed functional that penalizes the first and second derivatives equally. The higher the order of derivative, the more local smoothness over time; and lowest specified derivative controls the form of prior indifference. Default: c(0, 0, 1), which usually works well.
一个数值向量，它的每个元素是n，一个年龄组的时间趋势的平滑功能（离散）衍生的程度。元素k这个向量指的是(k-1)阶导数的时间趋势v年龄，其中0排除derviative，包括它，和值之间，包括衍生工具，但体重下降比例。该矢量的第一个元素对应的时间的趋势的衍生物的重量相对于0阶（恒等算子），所述第二权重的衍生物中的1阶（一阶导数），年龄等。例如，c(0, 1, 1)对应惩罚同样的第一和第二的衍生物的混合功能。较高的顺序衍生随着时间的推移，更多的本地平滑，最低指定的衍生工具控制之前，冷漠的形式。默认值：的c(0, 0, 1)，通常效果很好。
参数：Hat.t.deriv
A numeric vector, each element of which is n, the degree of a (discrete) derivative of the smoothness functional of age derivative with respect to time. Element k of this vector refers to the (k-1)th derivative of the age derivative with respect to time, where 0 excludes the derviative, 1 includes it, and values in between include the derivative but weight it down proportionally. The first element of the vector corresponds to the weight on the age derivative with respect to time of order 0 (the identity operator), the second to the weight on the derivative of order 1 (the 1st derivative), etc. For example, c(0, 1, 1) corresponds to a mixed functional that penalizes the first and second derivatives equally. The higher the order of derivative, the more local smoothness over time; and lowest specified derivative controls the form of prior indifference. Default: c(0, 0, 1), which usually works well.
一个数值向量，它的每个元素是n，衍生的年龄相对于时间的导数的平滑功能（离散）的程度。元k这个向量是指(k-1)阶导数的年龄衍生物相对于时间的，其中0排除derviative，1包括它，并在两者之间的值包括的衍生物，但重量比例。该矢量的第一个元素的重量对应的年龄衍生物相对于时间的0阶（恒等算子），所述第二的重量上的衍生物中的1阶（一阶导数），例如， c(0, 1, 1)对应的混合功能，同样惩罚的第一和第二衍生物。较高的顺序衍生随着时间的推移，更多的本地平滑，最低指定的衍生工具控制之前，冷漠的形式。默认值：的c(0, 0, 1)，通常效果很好。
参数：Hat.age.weight
A scalar or a numeric vector with weights that determines how much smoothing occurs for different age groups when smoothing over age and time. If set to 0 or NA, age groups are weighted equally in smoothing over time; if set to a nonzero scalar, the weight for age group a is set proportional to a^Ht.age.weight; if a vector of length A, the ath element is the weight of age group a. Default: 0.
出现一个标量或数字向量的权重，确定要达到的平滑不同年龄组时，平滑岁以上的时间。如果设置为0或NA，年龄组的平均加权平滑随着时间的推移，如果设置为一个非零的标量，重量岁年龄组的aa^Ht.age.weight比例设置，如果一个向量的长度为A，a个元素的权重年龄组a。默认值：0。
参数：Hat.time.weight
A scalar or a numeric vector with weights that determine how much smoothing occurs for different time periods when smoothing over age and time. If 0 or NA, time periods are weighted equally; if set to a nonzero scalar value, the weight for time period t in smoothing time periods is proportional to t^Ht.time.weight; if the argument is a vector of length T, the tth element is the weight of time period t. Default: 0.
一个标量或数字向量的权重，确定要达到的平滑平滑不同的时间段时，发生在年龄和时间。如果0或NA，权重相等的时间段，如果设置为一个非零的标值，时间段的权重t平滑时间段是成正比的t^Ht.time.weight;如果该参数是一个向量，长度为T，t个元素的权重的时间内t。默认值：0。
参数：Hct.sigma
A scalar which sets σ_t, the prior standard deviation of E(Y), which indicates how to smooth E(Y) over geographic areas, or NA to not smooth in this way. The parameter σ_ct is the expected prior standard deviation of E(Y) for a geographic area (varying over time periods and age groups, and with the standard deviations averaged over geographic areas). (A larger standard deviation represents more prior uncertainty, which allows the data to play a greater role.) Default: 0.3.
一个标量，它设置σ_t，前E(Y)，这表明如何顺利E(Y)过的GEO区域，或不适用不光滑，这样的标准差。参数σ_ct是E(Y)一个GEO区域（随时间变化的周期和年龄组，和GEO区域的标准偏差的平均值）的预期之前，标准差。 （一个较大的标准偏差表示更前的不确定性，使数据发挥更大的作用。）默认：0.3。
参数：Hct.sigma.sd
A scalar; the standard deviation of parameter Ht.sigma (for Gibbs sampling only). Default: 0.1.
标量的标准偏差的：参数Ht.sigma（只Gibbs抽样）。默认值：0.1。
参数：Hct.t.deriv
A numeric vector; controls whether smoothing the level or the time trend of E(Y) over geographic areas (both cannot presently be done simultaneously). To smooth the level of E(Y) over geographic areas, set to 1, the identity. To smooth the time trend, set this (as in Hat.t.deriv) to the weight of the partial derivative taken with respect to time in the standard smoothness functional for the prior. The use of the first or higher order partial derivatives are supported. Default: 1.
一个数字矢量控制是否平滑或时间趋势的E(Y)GEO区域（目前既不能同时进行）。以平滑的水平E(Y)以上的GEO区域，设置为1，的身份。为了平稳的时间趋势，设置此（在Hat.t.deriv）的偏导数的标准平滑功能之前就采取的重量。使用的一阶或高阶的偏导数的支持。默认值：1。
参数：Hct.time.weight
A scalar or a numeric vector with weights that determine how much smoothing occurs for different time periods when smoothing over geographic areas. If 0 or NA, time periods are weighted equally; if set to a nonzero scalar value, the weight for time period t in smoothing over areas is proportional to t^Hct.time.weight; if the argument is a vector of length T, the tth element is the weight of time period t. Default: 0.
一个标量或数字向量的权重，确定有多少不同的时间段时，发生平滑平滑过度的GEO区域。如果0或NA，权重相等的时间段，如果设置为一个非零的标值，时间段的权重t的平滑过的区域是成正比的t^Hct.time.weight;如果该参数是一个向量，长度为T，t个元素的权重的时间内t。默认值：0。
参数：LI.sigma.mean
A scalar; used in the likelihood and in the calculation of the priors in conjunction with Ha.sigma.sd, Hat.sigma.sd, Ht.sigma.sd, and Hct.sigma.sd. Default: 0.2.
标量; Ha.sigma.sd，Hat.sigma.sd，Ht.sigma.sd和Hct.sigma.sd结合使用的可能性和先验的计算。默认值：0.2。
参数：LI.sigma.sd
A scalar; the standard deviation of LI.sigma.mean used in the calculation of the priors. Default: 0.1.
标量; LI.sigma.mean先验的计算的标准差。默认值：0.1。
参数：nsample
A scalar; represents the number of iterations in the Gibbs algorithm bayes. Default: 500.
标量;代表数的迭代Gibbs算法bayes。默认值：500。
参数：low.pow
Boolean. Whether to include lower-power of explanatory variables in the simulation as derived from formula. For example y \sim x^4, if low.pow = TRUE, then x, x^2, x^3, x^4 will be included. Default: TRUE.
布尔值。是否包括低功耗的解释变量在模拟来自formula。例如 y \sim x^4如果low.pow=TRUE，那么x, x^2, x^3, x^4将被列入。默认值：TRUE。
参数：verbose
Boolean. Suppress verbose output. Default: FALSE
布尔值。禁止冗长的输出。默认值：FALSE
值----------Value----------
Returns a list of class "yourcast" containing the following components:
返回一个列表类的yourcast包含以下组件：
参数：call
The full call, including all command line options when yourcast was called.
完整的呼叫，包括所有命令行选项被称为yourcast时。
参数：userfile
The full userfile if it was specified.
完整的用户文件，如果它被指定。
参数：yhat
A list with the same cross-sectional elements as the input data, but with two columns: "y" for the observed dependent variable and "yhat" for the predicted values. These include both in-sample and out-of-sample values, as distinguished by the values of sample.frame.
具有相同的横截面的元素作为所输入的数据，但与两列：y的所观察到的因变量和yhat的预测值列表。这些措施包括在样品和外的样本值，区分sample.frame的值。
参数：coeff
A list with the same cross-sectional elements as the input data, elements of which are the estimated coefficients if calculated by the chosen model.
作为输入数据，其中的元素具有相同的横截面的元素的列表，如果计算出所选择的模型的估计系数。
参数：sigma
A list with the same cross-sectional elements as the input data, elements of which are the estimated standard error of the estimate of the regression (the standard deviation of the dependent variable given the explanatory variables).
作为输入数据，其中的元素具有相同的横截面的元素的列表是回归（给出的解释变量的因变量的标准偏差）的估计的估计的标准误差。
参数：aux
List. A list of summary information about the yourcast analysis used by plot.yourcast
列表。一个列表的摘要信息使用的yourcast分析的plot.yourcast
参数：params
Vector. Smoothing parameters used in model.
向量。平滑模型中使用的参数。
（作者）----------Author(s)----------
Federico Girosi <a href="mailto:girosi@rand.org">girosi@rand.org</a>;
Elena Villalon <a href="mailto:evillalon@iq.harvard.edu">evillalon@iq.harvard.edu</a>;
Gary King <a href="mailto:king@harvard.edu">king@harvard.edu</a>
参考文献----------References----------
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。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-2 07:39:58
