allFit {afex}R Documentation

Refit lmer model using multiple optimizers

Description

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), (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.

Usage

allFit(m, meth.tab = cbind(optimizer = rep(c("bobyqa", "Nelder_Mead",
  "optimx", "nloptwrap"), c(1, 1, 2, 2)), method = c("", "", "nlminb",
  "L-BFGS-B", "NLOPT_LN_NELDERMEAD", "NLOPT_LN_BOBYQA")), verbose = TRUE,
  maxfun = 1e+05, ...)

Arguments

m

a fitted model with lmer

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

verbose

print progress messages?

maxfun

number of iterations to allow for the optimization rountine.

...

further arguments passed to update.merMod such as data.

Details

Needs packages nloptr and optimx to try out all optimizers. optimx needs to be loaded explicitly using library or require.

Value

a list of fitted merMod objects

Author(s)

Ben Bolker

See Also

slice, slice2D in the bbmle package

Examples


## Not run: 

# basic usage
require(optimx)
gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
             data = cbpp, family = binomial)
gm_all <- allFit(gm1)
t(sapply(gm_all,fixef)) ## extract fixed effects
sapply(gm_all,logLik) ## log-likelihoods
sapply(gm_all,getME,"theta") ## theta parameters
!sapply(gm_all,inherits,"try-error") ## was fit OK?


## use allFit in combination with expand.re = TRUE
data("sk2011.2") # see example("mixed")
sk2_aff <- droplevels(sk2011.2[sk2011.2$what == "affirmation",])
sk_m2 <- mixed(response ~ instruction*inference*type+(inference*type||id), sk2_aff,
               expand_re = TRUE)
sk_m2
sk_m2_allFit <- allFit(sk_m2$full.model)
sk_m2_allFit # all fits fail

sk2_aff_b <- mixed(response ~ instruction*inference*type+(inference*type||id), sk2_aff,
               expand_re = TRUE, return = "data") # returns data only
sk_m2_allFit <- allFit(sk_m2$full.model, data = sk2_aff_b) # works now
t(sapply(sk_m2_allFit,fixef))
sapply(sk_m2_allFit,logLik)


## End(Not run)

[Package afex version 0.16-1 Index]