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.

Install the latest version of this package by entering the following in R:
install.packages("PEMM")
AuthorLin Chen <lchen@health.bsd.uchicago.edu> and Pei Wang <pwang@fhcrc.org>
Date of publication2014-01-25 00:37:55
MaintainerLin Chen <lchen@health.bsd.uchicago.edu>
LicenseGPL
Version1.0

View on CRAN

Files

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

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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