Use buildmer to fit big generalized additive models using gamm from package mgcv
Use buildmer to fit big generalized additive models using gamm from package mgcv
buildgamm( 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 |
... |
Additional options to be passed to |
The fixed and random effects are to be passed as a single formula in lme4 format. This is internally split up into the appropriate fixed and random parts.
Only a single grouping factor is allowed. The random-effect covariance matrix is always unstructured. If you want to use pdMat covariance structures, you must (a) not specify any lme4 random-effects term in the formula, and (b) specify your own custom random argument as part of the ... argument. Note that buildgamm will merely pass this through; no term reordering or stepwise elimination is done on a user-provided random argument.
library(buildmer)
model <- buildgamm(f1 ~ s(timepoint,by=following) + (following|participant) +
s(participant,timepoint,by=following,bs='fs'),data=vowels)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.