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.

Author
Lin Chen <lchen@health.bsd.uchicago.edu> and Pei Wang <pwang@fhcrc.org>
Date of publication
2014-01-25 00:37:55
Maintainer
Lin Chen <lchen@health.bsd.uchicago.edu>
License
GPL
Version
1.0

View on CRAN

Man pages

PEMM
A penalized EM algorithm incorporating missing-data mechanism...
PEMM_fun
A penalized EM algorithm incorporating missing-data mechanism...
sim_dat
A simulated multivariate data

Files in this package

PEMM
PEMM/NAMESPACE
PEMM/data
PEMM/data/sim_dat.rda
PEMM/R
PEMM/R/PEMM_fun.R
PEMM/MD5
PEMM/DESCRIPTION
PEMM/man
PEMM/man/PEMM_fun.Rd
PEMM/man/PEMM.Rd
PEMM/man/sim_dat.Rd