splmm (version 1.2.0)

splmm-package: tools:::Rd_package_title("splmm")

Description

tools:::Rd_package_description("splmm")

Author

tools:::Rd_package_author("splmm")

Maintainer: tools:::Rd_package_maintainer("splmm")

Details

The DESCRIPTION file: tools:::Rd_package_DESCRIPTION("splmm") tools:::Rd_package_indices("splmm")

Contains functions that fit linear mixed-effects models for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection.

References

Luoying Yang PhD thesis

SCHELLDORFER, J., BUHLMANN, P. and DE GEER, S.V. (2011), Estimation for High-Dimensional Linear Mixed-Effects Models Using L1-Penalization. Scandinavian Journal of Statistics, 38: 197-214. doi:10.1111/j.1467-9469.2011.00740.x

Examples

# \donttest{
## Use splmm on the Kenya school cognitive data set


data(cognitive)

x <- model.matrix(ravens ~schoolid+treatment+year+sex+age_at_time0
                  +height+weight+head_circ+ses+mom_read+mom_write
                  +mom_edu, cognitive)
z <- x

fit <- splmm(x=x,y=cognitive$ravens,z=z,grp=cognitive$id,lam1=0.1,
lam2=0.1,penalty.b="lasso", penalty.L="lasso")
summary(fit)
# }