GLMM-class {lme4} | R Documentation |
A fitted generalized linear mixed model.
Many methods for the "GLMM"
class simply recall the
generic on as(object, "lme")
which, in turn, often calls the
generic on the "rep"
component of the first argument. Thus the
methods actually are applied to an object of the "lme"
or
"ssclme"
class.
Objects are usually created by calls to the constructor function
GLMM
. They also can be created by calls of the form
new("GLMM", ...)
.
family
:family
for details.logLik
:"numeric"
value of the log-likelihood.fixef
:"numeric"
vector of fixed-effects
parameters.call
:facs
:list
of (possibly reordered) grouping
factors associated with the random effects.x
:x
to
lme
is TRUE
, a list
of model matrices
associated with the random effects, and the fixed effects with the
response appended. Otherwise, an empty list.model
:"data.frame"
)
for the model or, if the optional argument
model
to lme
is FALSE
, an empty frame.REML
:"logical"
indicator of the model having
been fit according to the REML criterion.rep
:"ssclme"
object representing the fitted
model.fitted
:"numeric"
vector of fitted values.residuals
:"numeric"
vector of raw residuals.
Class "lme"
, directly.
signature(x = "GLMM")
: Extract the variances,
standard deviations, and correlations of the random effects.signature(object = "GLMM")
: Perform an analysis
of variance.signature(object = "GLMM")
: Extract the parameters
that determine the relative precision matrices. The optional
argument unconst
determines if the constrained or
unconstrained parameterization is used.signature(object = "GLMM")
: Extract the
deviance as a numeric scalar. The optional argument REML
determines if the REML or ML criterion is used.signature(object = "GLMM")
: Extract the fitted
values as a numeric vector.signature(object = "GLMM")
: Extract the fixed
effects coefficients as a named numeric vector signature(x = "GLMM")
: Extract the formula of
the response and the fixed effects.signature(object = "GLMM")
: Extract the
log-likelihood.signature(x = "GLMM")
:signature(object = "GLMM")
: Extact the random
effects as a named list of numeric matrices.signature(object = "GLMM")
: Extract the
residuals as a numeric vector.signature(object = "GLMM")
: Print a concise
description of the object.signature(object = "GLMM")
: Create a summary
object of class "summary.lme"
.signature(object = "GLMM")
: Create an updated
fitted model.signature(object = "GLMM")
: Extract the variances
and covariances of the fixed-effects parameter estimates.