lme4 (version 1.1-15)

mkdevfun: Create Deviance Evaluation Function from Predictor and Response Module

Description

From a '>merMod object create an R function that takes a single argument, which is the new parameter value, and returns the deviance.

Usage

mkdevfun(rho, nAGQ = 1L, maxit = 100, verbose = 0, control = list())

Arguments

rho

an environment containing pp, a prediction module, typically of class '>merPredD and resp, a response module, e.g., of class '>lmerResp.

nAGQ

scalar integer - the number of adaptive Gauss-Hermite quadrature points. A value of 0 indicates that both the fixed-effects parameters and the random effects are optimized by the iteratively reweighted least squares algorithm.

maxit

scalar integer, currently only for GLMMs: the maximal number of Pwrss update iterations.

verbose

scalar logical: print verbose output?

control

list of control parameters, a subset of those specified by lmerControl (tolPwrss and compDev for GLMMs, tolPwrss for NLMMs)

Value

A function of one numeric argument.

Details

The function returned by mkdevfun evaluates the deviance of the model represented by the predictor module, pp, and the response module, resp.

For lmer model objects the argument of the resulting function is the variance component parameter, theta, with lower bound. For glmer or nlmer model objects with nAGQ = 0 the argument is also theta. However, when nAGQ > 0, the argument is c(theta, beta).

See Also

lmer, glmer and nlmer

Examples

# NOT RUN {
(dd <- lmer(Yield ~ 1|Batch, Dyestuff, devFunOnly=TRUE))
dd(0.8)
minqa::bobyqa(1, dd, 0)
# }