monomvn: Estimation for MVN and Student-t Data with Monotone Missingness

Estimation of multivariate normal (MVN) and student-t data of arbitrary dimension where the pattern of missing data is monotone. See Pantaleo and Gramacy (2010) <doi:10.48550/arXiv.0907.2135>. Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, the package can handle a nearly arbitrary amount of missing data. The current version supports maximum likelihood inference and a full Bayesian approach employing scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided.

Version:	1.9-20
Depends:	R (≥ 2.14.0), pls, lars, MASS
Imports:	quadprog, mvtnorm
Published:	2024-01-11
Author:	Robert B. Gramacy, with Fortran contributions from Cleve Moler (dpotri/LINPACK) as updated by Berwin A. Turlach (qpgen2/quadprog)
Maintainer:	Robert B. Gramacy <rbg at vt.edu>
License:	LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
URL:	https://bobby.gramacy.com/r_packages/monomvn/
NeedsCompilation:	yes
Materials:	ChangeLog
In views:	MissingData
CRAN checks:	monomvn results

Documentation:

Reference manual:

monomvn.pdf

Downloads:

Package source:	monomvn_1.9-20.tar.gz
Windows binaries:	r-devel: monomvn_1.9-20.zip, r-release: monomvn_1.9-20.zip, r-oldrel: monomvn_1.9-20.zip
macOS binaries:	r-release (arm64): monomvn_1.9-20.tgz, r-oldrel (arm64): monomvn_1.9-20.tgz, r-release (x86_64): monomvn_1.9-20.tgz, r-oldrel (x86_64): monomvn_1.9-20.tgz
Old sources:	monomvn archive

Reverse dependencies:

Reverse suggests:

flowml, hetGP, tidyfit

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