mvdpd: Robust DPD Methods for Casewise and Cellwise Contamination

Robust multivariate estimation based on multivariate, composite and componentwise Density Power Divergence (DPD) minimization in multivariate normal distribution for casewise and cellwise contamination. Robust estimation for multivariate ordered gamma model using multivariate and composite DPD minimization. See A. Ghosh, C. Agostinelli, and A. Basu (2026) A Composite Divergence Approach to Robust Multivariate Estimation under Cellwise and Casewise Contamination. <doi:10.48550/arXiv.2608.18914> for full details.

Version: 0.1-1
Depends: R (≥ 3.5.0)
Imports: MASS
Suggests: knitr, robustbase, cellWise, dplyr, ggplot2, reshape2, tidyr
Published: 2026-09-05
DOI: 10.32614/CRAN.package.mvdpd (may not be active yet)
Author: Claudio Agostinelli [aut, cre], Abhik Ghosh [aut], Ayanendranath Basu [aut]
Maintainer: Claudio Agostinelli <claudio.agostinelli at unitn.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: mvdpd citation info
CRAN checks: mvdpd results

Documentation:

Reference manual: mvdpd.html , mvdpd.pdf
Vignettes: mvnormDPD examples (source, R code)
mvogammaDPD examples (source, R code)

Downloads:

Package source: mvdpd_0.1-1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

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