Igamma.inv

get.lambda

get.regress

get.regress.C

adjust.elist.C

mvnpdf.C

rgig.C

bmonomvn.read.traces

read.DA.trace

read.muS.trace

addy

regress.ls

regress.lars

regress.pls

regress.ridge

regress.fact

opt.ridge

blasso.cleanup

bmonomvn.cleanup

check.start

check.QP

postprocess.QP

table2blasso

da.perm

add.pe.QP

 internal

monomvn-internal

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.

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monomvn-internal: Internal Monomvn Functions

Description

Arguments

Details