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cff-version: 1.2.0
message: 'To cite package "monomvn" in publications use:'
type: software
license: LGPL-2.0-only
title: 'monomvn: Estimation for MVN and Student-t Data with Monotone Missingness'
version: 1.9-21
doi: 10.32614/CRAN.package.monomvn
abstract: 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) <https://doi.org/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.
authors:
- family-names: Gramacy
  given-names: Robert B.
  email: rbg@vt.edu
repository: https://CRAN.R-project.org/package=monomvn
url: https://bobby.gramacy.com/r_packages/monomvn/
date-released: '2024-09-23'
contact:
- family-names: Gramacy
  given-names: Robert B.
  email: rbg@vt.edu