Package: monomvn
Type: Package
Title: Estimation for multivariate normal and Student-t data with
        monotone missingness
Version: 1.9-5
Date: 2014-05-21
Author: Robert B. Gramacy <rbgramacy@chicagobooth.edu>
Maintainer: Robert B. Gramacy <rbgramacy@chicagobooth.edu>
Description: Estimation of multivariate normal and student-t data of 
             arbitrary dimension where the pattern of missing data is monotone.
             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 (>= 2.10), pls, lars, MASS
Suggests: quadprog, mvtnorm
License: LGPL
URL: http://faculty.chicagobooth.edu/robert.gramacy/monomvn.html
Packaged: 2014-05-21 16:15:14 UTC; bobby
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-05-21 19:01:30
Built: R 3.1.0; x86_64-apple-darwin10.8.0; 2014-05-22 12:23:49 UTC; unix
Archs: monomvn.so.dSYM
