R语言 RMC包 MVfill()函数中文帮助文档(中英文对照)

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MVfill(RMC)
MVfill()所属R语言包：RMC

                                        Fill in missing values via a single imputation from the fitted model.
                                         填写从拟合模型通过一个单一插补缺失值。

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Inserts the fitted probability of observing the chained data used in estimation for the model (fm). To be used when the outcome variable is used as a covariate at subsequent stages of an analysis. The fitted probability is conditional on the nearest observed value in the chain.
插入嵌合观察已链接的估计中使用的数据的模型（调频）的概率。时要使用的协变量的结果变量被用作在随后的阶段分析。装在最近的观测值链中的概率是有条件的。


用法----------Usage----------


MVfill( fm, states=NULL, chain.id=NULL, X=NULL)



参数----------Arguments----------

参数： fm
a fitted model for the outcome that is required to be filled. Must be the result of a call to RMC.mod
一个模型拟合的结果是必须填写的。必须在调用RMC.mod的结果


参数： states
the outcome vector used to estimate the fitted model. Must be sequentially ordered within chains
结果矢量使用来估计拟合模型。必须按顺序责令限期链


参数： chain.id
a vector indicating which states belong to which chains
说明哪些国家属于一个向量链


参数： X
the design matrix for the model used to create fm. Column ordering must match that provided to fm and row ordering must match that in states (and chain.id)
设计矩阵的模型用于创建FM。列的顺序必须匹配提供FM和行的顺序必须符合国家（和chain.id）


值----------Value----------

<table summary="R valueblock"> <tr valign="top"><td> a matrix with number of columns equal to the number of categories of the outcome variable. Each column contains the observed value of that variable (if available) or the predicted probability of that observed variable (if no observation). Note that missing values at the ends of the chains are not imputed and are removed prior to estimation from RMC.mod.</td> <td> </td></tr></table>
<table summary="R valueblock"> <tr valign="top"> <TD> a matrix with number of columns equal to the number of categories of the outcome variable. Each column contains the observed value of that variable (if available) or the predicted probability of that observed variable (if no observation). Note that missing values at the ends of the chains are not imputed and are removed prior to estimation from RMC.mod. </ TD> <TD> </ TD> </ TR> </ TABLE>


（作者）----------Author(s)----------


Scott D. Foster



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。
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