Package: EMCC
Type: Package
Title: Evolutionary Monte Carlo (EMC) Methods for Clustering
Version: 1.3
Date: 2017-05-01
Author: Gopi Goswami <goswami@stat.harvard.edu>
Maintainer: Gopi Goswami <grgoswami@gmail.com>
Depends: R (>= 1.9.0), MASS, mclust, EMC
Description: Evolutionary Monte Carlo methods for clustering, temperature
        ladder construction and placement. This package implements methods
        introduced in Goswami, Liu and Wong (2007) <doi:10.1198/106186007X255072>.
        The paper above introduced probabilistic genetic-algorithm-style crossover
        moves for clustering. The paper applied the algorithm to several clustering
        problems including Bernoulli clustering, biological sequence motif
        clustering, BIC based variable selection, mixture of Normals clustering,
        and showed that the proposed algorithm performed better both as a sampler
        and as a stochastic optimizer than the existing tools, namely, Gibbs sampling,
        ``split-merge'' Metropolis-Hastings algorithm, K-means clustering, and the
        MCLUST algorithm (in the package 'mclust').
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2017-05-04 00:38:14 UTC; gopi
Repository: CRAN
Date/Publication: 2017-05-04 09:46:43 UTC
