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PEMM (version 1.0)

A Penalized EM algorithm incorporating missing-data mechanism

Description

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.

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Version

Install

install.packages('PEMM')

Monthly Downloads

9

Version

1.0

License

GPL

Maintainer

Lin Chen

Last Published

January 24th, 2014

Functions in PEMM (1.0)

PEMM

A penalized EM algorithm incorporating missing-data mechanism for multivariate parameter estimation
sim_dat

A simulated multivariate data
PEMM_fun

A penalized EM algorithm incorporating missing-data mechanism for multivariate parameter estimation