buildbam | R Documentation |
buildmer
to fit big generalized additive models using bam
from package mgcv
Use buildmer
to fit big generalized additive models using bam
from package mgcv
buildbam( formula, data = NULL, family = gaussian(), buildmerControl = buildmerControl() )
formula |
See the general documentation under |
data |
See the general documentation under |
family |
See the general documentation under |
buildmerControl |
Control arguments for buildmer — see the general documentation under |
To work around an issue in bam
, you must make sure that your data do not contain a variable named 'intercept'.
lme4
random effects are supported: they will be automatically converted using re2mgcv
.
As bam
uses PQL, only crit='F'
and crit='deviance'
(note that the latter is not a formal test) are supported for non-Gaussian errors.
buildmer-package
library(buildmer) model <- buildbam(f1 ~ s(timepoint,by=following) + s(participant,by=following,bs='re') + s(participant,timepoint,by=following,bs='fs'),data=vowels)
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