PEMM: A Penalized EM algorithm incorporating missing-data mechanism

This package provides functions to perform multivariate Gaussian parameter estimation based on data with abundance-dependent missingness. It implements a penalized Expectation-Maximization (EM) algorithm. The package is tailored for but not limited to proteomics data applications, in which a large proportion of the data are often missing-not-at-random with lower values (or absolute values) more likely to be missing.

Version: 1.0
Published: 2014-01-25
Author: Lin Chen and Pei Wang
Maintainer: Lin Chen <lchen at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: PEMM results


Reference manual: PEMM.pdf
Package source: PEMM_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: PEMM_1.0.tgz
OS X Mavericks binaries: r-oldrel: PEMM_1.0.tgz


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