monomvn (1.4)

Estimation for multivariate normal data with monotone missingness.

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 and beta implementation of a Bayesian version employing a Bayesian lasso. A fully functional standalone (beta) interface to the Bayesian lasso (from Park & Casella) and ridge regression with model selection via Reversible Jump is also provided

Author(s): Robert B. Gramacy <>

License: LGPL

Uses: lars, pls, accuracy, mvtnorm

Released about 10 years ago.