lme.groupedData(nlme)
lme.groupedData()所属R语言包：nlme
LME fit from groupedData Object
从伦敦金属交易所适合groupedData对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The response variable and primary covariate in formula(fixed) are used to construct the fixed effects model formula. This formula and the groupedData object are passed as the fixed and data arguments to lme.formula, together with any other additional arguments in the function call. See the documentation on lme.formula for a description of that function.
响应变量和formula(fixed)用于构建固定效应模型公式的主要协变量。这个公式和groupedData对象fixed和data参数传递lme.formula，连同任何其他额外的参数在函数调用。功能的描述文件lme.formula。
用法----------Usage----------
## S3 method for class 'groupedData'
lme(fixed, data, random, correlation, weights,
subset, method, na.action, control, contrasts, keep.data = TRUE)
参数----------Arguments----------
参数：fixed
a data frame inheriting from class groupedData.
继承类groupedData一个数据框。
参数：data
this argument is included for consistency with the generic function. It is ignored in this method function.
这种说法是包括通用功能的一致性。在此方法的功能被忽略。
参数：random
optionally, any of the following: (i) a one-sided formula of the form ~x1+...+xn | g1/.../gm, with x1+...+xn specifying the model for the random effects and g1/.../gm the grouping structure (m may be equal to 1, in which case no / is required). The random effects formula will be repeated for all levels of grouping, in the case of multiple levels of grouping; (ii) a list of one-sided formulas of the form ~x1+...+xn | g, with possibly different random effects models for each grouping level. The order of nesting will be assumed the same as the order of the elements in the list; (iii) a one-sided formula of the form ~x1+...+xn, or a pdMat object with a formula (i.e. a non-NULL value for formula(object)), or a list of such formulas or pdMat objects. In this case, the grouping structure formula will be derived from the data used to fit the linear mixed-effects model, which should inherit from class groupedData; (iv) a named list of formulas or pdMat objects as in (iii), with the grouping factors as names. The order of nesting will be assumed the same as the order of the order of the elements in the list; (v) an reStruct object. See the documentation on pdClasses for a description of the available pdMat classes. Defaults to a formula consisting of the right hand side of fixed.
可选以下任：（一）片面的公式的形式~x1+...+xn | g1/.../gm，x1+...+xn指定模型的随机效应和g1/.../gm分组结构（<X >可能等于1，在这种情况下，没有m需要）。随机效应的公式将重复所有级别的分组，在分组的多层次的情况下;（ii）为每个分组形式/可能有不同的随机效应模型，片面的公式列表水平。嵌套的顺序将被假设为列表中的元素的顺序相同;（三）片面的公式与公式的形式~x1+...+xn | g或~x1+...+xn对象（即非pdMat值NULL），或如公式或formula(object)对象名单。在这种情况下，分组结构公式将来自用于拟合的线性混合效应模型的数据，应该继承类pdMat;（四）一个公式或groupedData对象的命名列表（三），作为名称的分组因素。嵌套的顺序将被假定为顺序列表中的元素的顺序相同;（V）pdMat的对象。可用reStruct类的描述，请参阅文件pdClasses。默认为公式右侧pdMat组成。
参数：correlation
an optional corStruct object describing the within-group correlation structure. See the documentation of corClasses for a description of the available corStruct classes. Defaults to NULL, corresponding to no within-group correlations.
一个可选的corStruct对象，它描述的组内相关结构。可用corClasses类的描述，请参阅文件corStruct。 NULL默认值，相应的组内没有相关。
参数：weights
an optional varFunc object or one-sided formula describing the within-group heteroscedasticity structure. If given as a formula, it is used as the argument to varFixed, corresponding to fixed variance weights. See the documentation on varClasses for a description of the available varFunc classes. Defaults to NULL, corresponding to homoscedastic within-group errors.
一个可选的varFunc对象或片面的公式描述组内异方差结构。如果给出一个公式，它是用来作为的varFixed，相应的固定方差权重的参数。可用varClasses类的描述，请参阅文件varFunc。默认NULL，对应于同方差组内的错误。
参数：subset
an optional expression indicating the subset of the rows of data that should be used in the fit. This can be a logical vector, or a numeric vector indicating which observation numbers are to be included, or a character vector of the row names to be included. All observations are included by default.
一个可选的表达式表示data，应适合使用的行的子集。这可以是一个逻辑向量，或一个数字的向量，被列入观察数字或字符向量的行名被列入。所有的意见，包括默认情况下。
参数：method
a character string. If "REML" the model is fit by maximizing the restricted log-likelihood. If "ML" the log-likelihood is maximized. Defaults to "REML".
一个字符串。如果"REML"模型适合最大限度地限制日志的可能性。如果"ML"日志的可能性最大化。 "REML"默认。
参数：na.action
a function that indicates what should happen when the data contain NAs. The default action (na.fail) causes lme to print an error message and terminate if there are any incomplete observations.
一个函数，它表示数据时，包含NA的，应该发生什么。默认动作（na.fail）导致lme打印一个错误消息并终止，如果有任何不完整的意见。
参数：control
a list of control values for the estimation algorithm to replace the default values returned by the function lmeControl. Defaults to an empty list.
估计算法的控制值的列表来替换默认的返回值的函数lmeControl。默认为一个空列表。
参数：contrasts
an optional list. See the contrasts.arg of model.matrix.default.
可选列表。参见contrasts.argmodel.matrix.default。
参数：keep.data
logical: should the data argument (if supplied and a data frame) be saved as part of the model object?
逻辑：data参数（如果提供的数据框）作为模型对象的一部分保存？
值----------Value----------
an object of class lme representing the linear mixed-effects model fit. Generic functions such as print, plot and summary have methods to show the results of the fit. See lmeObject for the components of the fit. The functions resid, coef, fitted, fixed.effects, and random.effects can be used to extract some of its components.
一个类的对象lme代表线性混合效应模型拟合。通用功能，如print，plot和summary方法来显示合适的结果。看到lmeObject适合的组成部分。职能resid，coef，fitted，fixed.effects，random.effects可以用来提取其组成部分。
作者（S）----------Author(s)----------
Jose Pinheiro and Douglas Bates <a href="mailto:bates@stat.wisc.edu">bates@stat.wisc.edu</a>
参考文献----------References----------
M.J. and Bates, D.M. (1988). The model formulation is described in Laird, N.M. and Ware, J.H. (1982). The variance-covariance parametrizations are described in Pinheiro, J.C. and Bates., D.M. (1996). The different correlation structures available for the <code>correlation</code> argument are described in Box, G.E.P., Jenkins, G.M., and Reinsel G.C. (1994), Littel, R.C., Milliken, G.A., Stroup, W.W., and Wolfinger, R.D. (1996), and Venables, W.N. and Ripley, B.D. (1997). The use of variance functions for linear and nonlinear mixed effects models is presented in detail in Davidian, M. and Giltinan, D.M. (1995).
Analysis: Forecasting and Control", 3rd Edition, Holden-Day.
for Repeated Measurement Data", Chapman and Hall.
Longitudinal Data", Biometrics, 38, 963-974.
Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data", Journal of the American Statistical Association, 83, 1014-1022.
"SAS Systems for Mixed Models", SAS Institute.
Parametrizations for Variance-Covariance Matrices", Statistics and Computing, 6, 289-296.
in S and S-PLUS", Springer.
S-plus", 2nd Edition, Springer-Verlag.
参见----------See Also----------
lme, groupedData,
lme，groupedData
举例----------Examples----------
fm1 <- lme(Orthodont)
summary(fm1)
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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 2012-2-16 21:22:54
