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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
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Package details |
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| Author | Lin Chen <lchen@health.bsd.uchicago.edu> and Pei Wang <pwang@fhcrc.org> |
| Maintainer | Lin Chen <lchen@health.bsd.uchicago.edu> |
| License | GPL |
| Version | 1.0 |
| Package repository | View on CRAN |
| Installation |
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