MaciejDanko/pclm: Penalized Composite Linear Models (PCLMs)
Version 2017.09.19

The PCLM method is based on the composite link model, with a penalty added to ensure the smoothness of the target distribution. Estimates are obtained by maximizing a penalized likelihood. This maximization is performed efficiently by a version of the iteratively reweighted least-squares algorithm. Optimal values of the smoothing parameter are chosen by minimizing Bayesian or Akaike’ s Information Criterion [From Rizzi et al. 2015 abstract].

Getting started

Package details

AuthorMaciej J. Danko <[email protected]> <[email protected]>, Marius Pascariu <[email protected]>, Silvia Rizzi <[email protected]>,
MaintainerMarius Pascariu <[email protected]>, Maciej J. Danko <[email protected]> <[email protected]>
LicenseGPL-2
Version2017.09.19
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("MaciejDanko/pclm")
MaciejDanko/pclm documentation built on Sept. 21, 2017, 12:35 a.m.