allFit

0th

Percentile

Refit a fitted model with all available optimizers

Attempt to re-fit a [g]lmer model with a range of optimizers. The default is to use all known optimizers for R that satisfy the requirements (do not require explicit gradients, allow box constraints), in three categories; (i) built-in (minqa::bobyqa, lme4::Nelder_Mead, nlminbwrap), (ii) wrapped via optimx (most of optimx's optimizers that allow box constraints require an explicit gradient function to be specified; the two provided here are really base R functions that can be accessed via optimx, (iii) wrapped via nloptr; (iv)

Keywords
models
Usage
allFit(m, meth.tab = NULL, data=NULL,
        verbose = TRUE,
        show.meth.tab = FALSE,
        maxfun = 1e5,
	parallel = c("no", "multicore", "snow"),
	ncpus = getOption("allFit.ncpus", 1L), cl = NULL)
Arguments
m

a fitted model

meth.tab

a matrix (or data.frame) with columns

method

the name of a specific optimization method to pass to the optimizer (leave blank for built-in optimizers)

optimizer

the optimizer function to use

data

data to be included with result (for later debugging etc.)

verbose

logical: report progress in detail?

show.meth.tab

logical: return table of methods?

maxfun

passed as part of optCtrl (see lmeControl)

parallel

The type of parallel operation to be used (if any). If missing, the default is taken from the option "boot.parallel" (and if that is not set, "no").

ncpus

integer: number of processes to be used in parallel operation: typically one would choose this to be the number of available CPUs.

cl

An optional parallel or snow cluster for use if parallel = "snow". If not supplied, a cluster on the local machine is created for the duration of the boot call.

Value

a list of fitted merMod objects (unless show.meth.tab is specified, in which case a data frame of methods is returned)

Note

If you are using parallel="snow", you will need to run clusterEvalQ(cl,library("lme4")) before calling allFit to make sure that the lme4 package is loaded on all of the workers

See Also

slice,slice2D from the bbmle package

Aliases
  • allFit
Examples
# NOT RUN {
library(lme4)
gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
             data = cbpp, family = binomial)
## show available methods
allFit(show.meth.tab=TRUE) 
gm_all <- allFit(gm1)
ss <- summary(gm_all)
ss$fixef               ## extract fixed effects
ss$llik                ## log-likelihoods
ss$sdcor               ## SDs and correlations
ss$theta               ## Cholesky factors
ss$which.OK            ## which fits worked
# }
Documentation reproduced from package lme4, version 1.1-21, License: GPL (>= 2)

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