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: 2024-09-23 13:43:44 UTC; bobby
Author: Robert B. Gramacy [aut, cre] (with Fortran contributions from Cleve
    Moler (dpotri/LINPACK) as updated by Berwin A. Turlach
    (qpgen2/quadprog))
Repository: CRAN
Date/Publication: 2024-09-23 14:10:05 UTC
Built: R 4.5.2; x86_64-w64-mingw32; 2025-12-03 03:57:33 UTC; windows
Archs: x64
