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.

Getting started

Package details

AuthorLin Chen <> and Pei Wang <>
MaintainerLin Chen <>
Package repositoryView on CRAN
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PEMM documentation built on May 2, 2019, 6:34 a.m.