devfun2 {lme4} | R Documentation |
The deviance is profiled with respect to the fixed-effects parameters but not with respect to sigma; that is, the function takes parameters for the variance-covariance parameters and for the residual standard deviation. The random-effects variance-covariance parameters are on the standard deviation/correlation scale, not the theta (Cholesky factor) scale.
devfun2(fm, useSc, transfuns = list(from.chol = Cv_to_Sv, to.chol = Sv_to_Cv, to.sd = identity), ...)
fm |
a fitted model of class ‘merMod’ |
useSc |
(logical) whether a scale parameter is used |
transfuns |
functions for converting parameters to and from the Cholesky-factor scale |
... |
arguments passed to the internal |
Returns a function that takes a vector of standard deviations and correlations and returns the deviance (or REML criterion). The function has additional attributes
a named vector giving the parameter values at the optimum
the deviance at the optimum (not the
REML criterion, even if the original model was fitted using
REML=TRUE
)
the optimal variance-covariance parameters on the “theta” (Cholesky factor) scale
standard errors of fixed effect parameters
m1 <- lmer(Reaction~Days+(Days|Subject),sleepstudy) dd <- devfun2(m1,useSc=TRUE) pp <- attr(dd,"optimum") ## extract variance-covariance and residual std dev parameters sigpars <- pp[grepl("^\\.sig",names(pp))] all.equal(unname(dd(sigpars)),deviance(refitML(m1)))