If the random effects names defined in
random are a subset of
lmList object coefficient names, initial estimates for the
covariance matrix of the random effects are obtained (overwriting any
values given in
formula(fixed) and the
data argument in the calling sequence used to obtain
fixed are passed as the
lme.formula, together with any other additional arguments in
the function call. See the documentation on
lme.formula for a
description of that function.
# S3 method for lmList lme(fixed, data, random, correlation, weights, subset, method, na.action, control, contrasts, keep.data)
an object inheriting from class
representing a list of
lm fits with a common model.
this argument is included for consistency with the generic function. It is ignored in this method function.
an optional one-sided linear formula with no conditioning
expression, or a
pdMat object with a
attribute. Multiple levels of grouping are not allowed with this
method function. Defaults to a formula consisting of the right hand
corStruct object describing the
within-group correlation structure. See the documentation of
corClasses for a description of the available
classes. Defaults to
corresponding to no within-group correlations.
varFunc object or one-sided formula
describing the within-group heteroscedasticity structure. If given as
a formula, it is used as the argument to
corresponding to fixed variance weights. See the documentation on
varClasses for a description of the available
classes. Defaults to
NULL, corresponding to homoscedastic
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.
a character string. If
"REML" the model is fit by
maximizing the restricted log-likelihood. If
log-likelihood is maximized. Defaults to
a function that indicates what should happen when the
NAs. The default action (
lme to print an error message and terminate if there are any
a list of control values for the estimation algorithm to
replace the default values returned by the function
Defaults to an empty list.
an optional list. See the
logical: should the
data argument (if supplied
and a data frame) be saved as part of the model object?
an object of class
lme representing the linear mixed-effects
model fit. Generic functions such as
summary have methods to show the results of the fit. See
lmeObject for the components of the fit. The functions
random.effects can be used to extract some of its components.
The computational methods follow the general framework of Lindstrom
and Bates (1988). The model formulation is described in Laird and Ware
(1982). The variance-covariance parametrizations are described in
Pinheiro and Bates (1996). The different correlation structures
available for the
correlation argument are described in Box,
Jenkins and Reinse (1994), Littel et al (1996), and Venables and
Ripley, (2002). The use of variance functions for linear and nonlinear
mixed effects models is presented in detail in Davidian and Giltinan
Box, G.E.P., Jenkins, G.M., and Reinsel G.C. (1994) "Time Series Analysis: Forecasting and Control", 3rd Edition, Holden--Day.
Davidian, M. and Giltinan, D.M. (1995) "Nonlinear Mixed Effects Models for Repeated Measurement Data", Chapman and Hall.
Laird, N.M. and Ware, J.H. (1982) "Random-Effects Models for Longitudinal Data", Biometrics, 38, 963--974.
Lindstrom, M.J. and Bates, D.M. (1988) "Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data", Journal of the American Statistical Association, 83, 1014--1022.
Littel, R.C., Milliken, G.A., Stroup, W.W., and Wolfinger, R.D. (1996) "SAS Systems for Mixed Models", SAS Institute.
Pinheiro, J.C. and Bates., D.M. (1996) "Unconstrained Parametrizations for Variance-Covariance Matrices", Statistics and Computing, 6, 289--296.
Venables, W.N. and Ripley, B.D. (2002) "Modern Applied Statistics with S", 4th Edition, Springer-Verlag.