Package: monomvn
Type: Package
Title: Estimation for multivariate normal data with monotone missingness
Version: 1.1-1
Date: 2007-08-21
Author: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Maintainer: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Description: Estimation of multivariate normal 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 an (almost)
arbitrary amount of missing data.  The current version supports
maximum likelihood inference.  Future versions will provide a means
of sampling from a Bayesian posterior.
Depends: R (>= 2.5), pls, lars, MASS
Suggests: mvtnorm, accuracy
License: LGPL (Lesser GNU Public License)
URL: http://www.statslab.cam.ac.uk/~bobby/monomvn.html
Packaged: Wed Aug 22 11:28:52 2007; bobby

Package: monomvn
Type: Package
Title: Estimation for multivariate normal data with monotone missingness
Version: 1.1-2
Date: 2007-10-31
Author: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Maintainer: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Description: Estimation of multivariate normal 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 an (almost)
arbitrary amount of missing data.  The current version supports
maximum likelihood inference.  Future versions will provide a means
of sampling from a Bayesian posterior.
Depends: R (>= 2.5), pls, lars, MASS
Suggests: mvtnorm, accuracy
License: LGPL (Lesser GNU Public License)
URL: http://www.statslab.cam.ac.uk/~bobby/monomvn.html
Packaged: Wed Oct 31 12:17:54 2007; bobby

Package: monomvn
Type: Package
Title: Estimation for multivariate normal data with monotone missingness
Version: 1.1-4
Date: 2007-11-11
Author: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Maintainer: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Description: Estimation of multivariate normal 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 an (almost)
arbitrary amount of missing data.  The current version supports
maximum likelihood inference.  Future versions will provide a means
of sampling from a Bayesian posterior.
Depends: R (>= 2.5), pls, lars, MASS
Suggests: mvtnorm, accuracy
License: LGPL
URL: http://www.statslab.cam.ac.uk/~bobby/monomvn.html
Packaged: Sun Nov 11 19:14:48 2007; bobby