Package: monomvn
Type: Package
Title: Estimation for MVN and Student-t Data with Monotone Missingness
Version: 1.9-21
Date: 2024-09-23
Authors@R: c(person(given = c("Robert", "B."),
                      family = "Gramacy",
                      role = c("aut", "cre"),
                      email = "rbg@vt.edu",
                      comment = "with Fortran contributions from Cleve Moler (dpotri/LINPACK) as updated by Berwin A. Turlach (qpgen2/quadprog)"))
Maintainer: Robert B. Gramacy <rbg@vt.edu>
Description: 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.
Depends: R (>= 2.14.0), pls, lars, MASS
Imports: quadprog, mvtnorm
License: LGPL
URL: https://bobby.gramacy.com/r_packages/monomvn/
NeedsCompilation: yes
Packaged: 2026-07-04 09:01:36 UTC; root
Author: Robert B. Gramacy [aut, cre] (with Fortran contributions from
        Cleve Moler (dpotri/LINPACK) as updated by Berwin A. Turlach
        (qpgen2/quadprog))
Repository: https://rbgramacy.r-universe.dev
Date/Publication: 2024-09-24 03:02:35 UTC
RemoteUrl: https://github.com/cran/monomvn
RemoteRef: HEAD
RemoteSha: 32ab4cac6c80db697db105aac3a9679697ed4ec1