Package: PARSE
Type: Package
Title: Model-Based Clustering with Regularization Methods for
        High-Dimensional Data
Version: 0.1.0
Date: 2016-06-10
Author: Lulu Wang, Wen Zhou, Jennifer Hoeting
Maintainer: Lulu Wang <wanglulu@stat.colostate.edu>
Description: Model-based clustering and identifying informative features based on regularization methods. The package includes three regularization methods - PAirwise Reciprocal fuSE (PARSE) penalty proposed by Wang, Zhou and Hoeting (2016), the adaptive L1 penalty (APL1) and the adaptive pairwise fusion penalty (APFP). Heatmaps are included to shown the identification of informative features.
License: CC0
LazyData: TRUE
Depends: R (>= 3.0.0)
Imports: stats, mvtnorm, gplots, foreach, doParallel, grDevices, utils
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-06-10 19:42:13 UTC; luluwang
Repository: CRAN
Date/Publication: 2016-06-11 09:42:05
