MaciejDanko/pclm: Penalized Composite Linear Models (PCLMs)
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
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Package details |
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| Author | Maciej J. Danko <danko@demogr.mpg.de> <maciej.danko@gmail.com>, Marius Pascariu <mpascariu@health.sdu.dk>, Silvia Rizzi <srizzi@health.sdu.dk>, |
| Maintainer | Marius Pascariu <mpascariu@health.sdu.dk>, Maciej J. Danko <danko@demogr.mpg.de> <maciej.danko@gmail.com> |
| License | GPL-2 |
| Version | 2017.09.19 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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