monomvn-package {monomvn}R Documentation

Estimation for Multivariate Normal Data with Monotone Missingness

Description

Estimation of multivariate normal data of arbitrary dimension where the pattern of missing data is monotone. Through the use of partial least squares and principal component regressions, 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.

Details

For a fuller overview including a complete list of functions, demos and vignettes, please use help(package="tgp").

Author(s)

Robert B. Gramacy bobby@statslab.cam.ac.uk

Maintainer: Robert B. Gramacy bobby@statslab.cam.ac.uk

References

Statistical Analysis with Missing Data, Second Edition. Roderick J.A. Little and Donald B. Rubin. Wilely. (2002)

http://www.statslab.cam.ac.uk/~bobby/monomvn.html

See Also

monomvn, norm, mvnmle


[Package monomvn version 1.1-4 Index]