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.
| Version: | 1.0 |
| Published: | 2014-01-25 |
| Author: | Lin Chen and Pei Wang |
| Maintainer: | Lin Chen <lchen at health.bsd.uchicago.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| CRAN checks: | PEMM results |
| Reference manual: | PEMM.pdf |
| Package source: | PEMM_1.0.tar.gz |
| Windows binaries: | r-devel: PEMM_1.0.zip, r-release: PEMM_1.0.zip, r-oldrel: PEMM_1.0.zip |
| macOS binaries: | r-release: PEMM_1.0.tgz, r-oldrel: PEMM_1.0.tgz |
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