nlmeObject: Fitted nlme Object
Description
An object returned by the nlme function, inheriting from class
nlme, also inheriting from class lme, and representing a
fitted nonlinear mixed-effects model. Objects of this class have
methods for the generic functions anova, coef,
fitted, fixed.effects, formula, getGroups,
getResponse, intervals, logLik, pairs,
plot, predict, print, random.effects,
residuals, summary, and update.Value
- The following components must be included in a legitimate
nlme
object. - apVaran approximate covariance matrix for the
variance-covariance coefficients. If
apVar = FALSE in the list
of control values used in the call to nlme, this
component is equal to NULL. - calla list containing an image of the
nlme call that
produced the object. - coefficientsa list with two components,
fixed and
random, where the first is a vector containing the estimated
fixed effects and the second is a list of matrices with the estimated
random effects for each level of grouping. For each matrix in the
random list, the columns refer to the random effects and the
rows to the groups. - contrastsa list with the contrasts used to represent factors
in the fixed effects formula and/or random effects formula. This
information is important for making predictions from a new data
frame in which not all levels of the original factors are
observed. If no factors are used in the nlme model, this component
will be an empty list.
- dimsa list with basic dimensions used in the nlme fit,
including the components
N - the number of observations in
the data, Q - the number of grouping levels, qvec -
the number of random effects at each level from innermost to
outermost (last two values are equal to zero and correspond to the
fixed effects and the response), ngrps - the number of groups
at each level from innermost to outermost (last two values are one
and correspond to the fixed effects and the response), and
ncol - the number of columns in the model matrix for each
level of grouping from innermost to outermost (last two values are
equal to the number of fixed effects and one). - fitteda data frame with the fitted values as columns. The
leftmost column corresponds to the population fixed effects
(corresponding to the fixed effects only) and successive columns
from left to right correspond to increasing levels of grouping.
- fixDFa list with components
X and terms
specifying the denominator degrees of freedom for, respectively,
t-tests for the individual fixed effects and F-tests for the
fixed-effects terms in the models. - groupsa data frame with the grouping factors as
columns. The grouping level increases from left to right.
- logLikthe (restricted) log-likelihood at convergence.
- mapa list with components
fmap, rmap,
rmapRel, and bmap, specifying various mappings for the
fixed and random effects, used to generate predictions from the
fitted object. - methodthe estimation method: either
"ML" for maximum
likelihood, or "REML" for restricted maximum likelihood. - modelStructan object inheriting from class
nlmeStruct,
representing a list of mixed-effects model components, such
as reStruct, corStruct, and varFunc objects. - numIterthe number of iterations used in the iterative
algorithm.
- residualsa data frame with the residuals as columns. The
leftmost column corresponds to the population residuals
and successive columns from left to right correspond to increasing
levels of grouping.
- sigmathe estimated within-group error standard deviation.
- varFixan approximate covariance matrix of the
fixed effects estimates.