Renvlp: Computing Envelope Estimators

Provides a general routine, envMU(), which allows estimation of the M envelope of span(U) given root n consistent estimators of M and U. The routine envMU() does not presume a model. This package implements response envelopes (env()), partial response envelopes (penv()), envelopes in the predictor space (xenv()), heteroscedastic envelopes (henv()), simultaneous envelopes (stenv()), scaled response envelopes (senv()), scaled envelopes in the predictor space (sxenv()), groupwise envelopes (genv()), weighted envelopes (weighted.env(), weighted.penv() and weighted.xenv()), envelopes in logistic regression (logit.env()), and envelopes in Poisson regression (pois.env()). For each of these model-based routines the package provides inference tools including bootstrap, cross validation, estimation and prediction, hypothesis testing on coefficients are included except for weighted envelopes. Tools for selection of dimension include AIC, BIC and likelihood ratio testing. Background is available at Cook, R. D., Forzani, L. and Su, Z. (2016) <doi:10.1016/j.jmva.2016.05.006>. Optimization is based on a clockwise coordinate descent algorithm.

Version: 2.5
Imports: Rsolnp, stats
Suggests: MASS, knitr
Published: 2018-01-18
Author: Minji Lee, Zhihua Su
Maintainer: Minji Lee <mlee9 at>
License: GPL-2
NeedsCompilation: no
CRAN checks: Renvlp results


Reference manual: Renvlp.pdf
Vignettes: EnvelopeEstimation
Package source: Renvlp_2.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: Renvlp_2.5.tgz, r-oldrel: Renvlp_2.5.tgz


Please use the canonical form to link to this page.