merMCMC-class {lme4} | R Documentation |
Objects of class "merMCMC"
are Markov chain Monte Carlo samples
from the distribution of the parameters of a fitted mixed-effects
model.
Objects can be created by calls of the form new("merMCMC", ...)
or, more commonly, via the mer
method for the generic
mcmcsamp
function.
Gp
:Gp
slot of the original
mer
objectST
:ST
slot of the mer
objectcall
:mer
objectdeviance
:dims
:dims
slot of the original
mer
objectfixef
:nc
:dims["nf"]
. The
number of columns of random effects in each term.ranef
:saveb = TRUE
is specified in
the call to mcmcsamp
. Consider the size of this
matrix, which could be very large, before setting saveb = TRUE
.sigma
:numeric(0)
if dims["useSc"]
is FALSE
.signature(object = "merMCMC")
: use the
chain to calculate Highest Posterior Density (HPD) intervals of a
given empirical probability content for the model parameters. See
HPDinterval
.signature(x = "merMCMC")
: transform the
ST
and sigma
slots to some combination of variances,
covariances, standard deviations and correlations. See
VarCorr
for details.signature(x = "merMCMC")
: returns the
fixef-effects and variance-covariance parameters from the chain in
the form of a data frame. The type
argument for the
VarCorr
method can be passed to this method to
select the type of variance-covariance parameters returned.signature(x = "merMCMC")
: Same as the
as.data.frame
method described above but returning a matrix.signature(from = "merMCMC", to = "data.frame")
:
Same as the as.data.frame
method.signature(object = "merMCMC")
: plot
empirical densities for the parameters from the chain. See also
densityplot
.signature(object = "merMCMC")
: plot
quantile-quantile plots for the parameters from the sample in the
chain. See also qqmath
.signature(object = "merMCMC")
: plot
traces of the parameter samples in the chain.
mcmcsamp
produces these objects,
lmer
, glmer
and nlmer
produce the mer
objects.
showClass("merMCMC")