Given independent and identically distributed observations X(1), ..., X(n), this package allows to compute a concave, piecewise linear function phi on [X(1), X(n)] with knots only in {X(1), X(2), ..., X(n)} such that L(phi) = sum_{i=1}^n W(i)*phi(X(i)) - int_{X(1)}^{X(n)} exp(phi(x)) dx is maximal, for some weights W(1), ..., W(n) s.t. sum_{i=1}^n W(i) = 1. According to the results in Duembgen and Rufibach (2008), this function phi maximizes the ordinary log-likelihood sum_{i=1}^n W(i)*phi(X(i)) under the constraint that phi is concave. The corresponding function exp(phi) is a log-concave probability density. Two algorithms are offered: An active set algorithm and one based on the pool-adjacent-violaters algorithm.
| Version: | 1.3.2 |
| Date: | 2008-07-14 |
| Author: | Kaspar Rufibach and Lutz Duembgen |
| Maintainer: | Kaspar Rufibach <kaspar.rufibach at gmail.com> |
| License: | GPL version 2 or newer |
| URL: | http://www.staff.unibe.ch/duembgen |
| CRAN checks: | logcondens results |
Downloads:
| Package source: | logcondens_1.3.2.tar.gz |
| MacOS X binary: | logcondens_1.3.2.tgz |
| Windows binary: | logcondens_1.3.2.zip |
| Reference manual: | logcondens.pdf |
| Old sources: | logcondens archive |