buildgamm: Use 'buildmer' to fit big generalized additive models using...

In cvoeten/buildmer: Stepwise Elimination and Term Reordering for Mixed-Effects Regression

Use buildmer to fit big generalized additive models using gamm from package mgcv

Description

Use buildmer to fit big generalized additive models using gamm from package mgcv

Usage

buildgamm(
  formula,
  data = NULL,
  family = gaussian(),
  buildmerControl = buildmerControl()
)

Arguments

formula	See the general documentation under buildmer-package
data	See the general documentation under buildmer-package
family	See the general documentation under buildmer-package
buildmerControl	Control arguments for buildmer — see the general documentation under buildmerControl

Details

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 in the args list in buildmerControl. Note that buildgamm will merely pass this through; no term reordering or stepwise elimination is done on a user-provided random argument.

See Also

buildmer-package

Examples

library(buildmer)
model <- buildgamm(f1 ~ s(timepoint,by=following) + (following|participant) +
       s(participant,timepoint,by=following,bs='fs'),data=vowels)

cvoeten/buildmer documentation built on March 3, 2023, 3:25 p.m.