Functions capable of performing efficient design matrix free penalized estimation in large scale 2 and 3dimensional generalized linear array model framework. The generic glamlasso() function solves the penalized maximum likelihood estimation (PMLE) problem in a pure generalized linear array model (GLAM) as well as in a GLAM containing a nontensor component. Currently Lasso or Smoothly Clipped Absolute Deviation (SCAD) penalized estimation is possible for the followings models: The Gaussian model with identity link, the Binomial model with logit link, the Poisson model with log link and the Gamma model with log link. Furthermore this package also contains two functions that can be used to fit special cases of GLAMs, see glamlassoRR() and glamlassoS(). The procedure underlying these functions is based on the gdpg algorithm from Lund et al. (2017)
Package details 


Author  Adam Lund 
Date of publication  20180119 14:48:29 UTC 
Maintainer  Adam Lund <[email protected]> 
License  GPL3 
Version  3.0 
Package repository  View on CRAN 
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