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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, partial response envelopes, envelopes in the predictor space, heteroscedastic envelopes, simultaneous envelopes, scaled response envelopes, scaled envelopes in the predictor space, groupwise envelopes, weighted envelopes, envelopes in logistic regression, envelopes in Poisson regression envelopes in function-on-function linear regression, envelope-based Partial Partial Least Squares, envelopes with non-constant error covariance, envelopes with t-distributed errors, reduced rank envelopes and reduced rank envelopes with non-constant error covariance. 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: 3.4.5
Depends: R (≥ 3.5.0)
Imports: Rsolnp, stats, orthogonalsplinebasis, pls, matrixcalc, Matrix
Suggests: MASS
Published: 2023-10-10
DOI: 10.32614/CRAN.package.Renvlp
Author: Minji Lee, Zhihua Su
Maintainer: Minji Lee <minjilee101 at gmail.com>
License: GPL-2
NeedsCompilation: no
CRAN checks: Renvlp results

Documentation:

Reference manual: Renvlp.pdf

Downloads:

Package source: Renvlp_3.4.5.tar.gz
Windows binaries: r-devel: Renvlp_3.4.5.zip, r-release: Renvlp_3.4.5.zip, r-oldrel: Renvlp_3.4.5.zip
macOS binaries: r-release (arm64): Renvlp_3.4.5.tgz, r-oldrel (arm64): Renvlp_3.4.5.tgz, r-release (x86_64): Renvlp_3.4.5.tgz, r-oldrel (x86_64): Renvlp_3.4.5.tgz
Old sources: Renvlp archive

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.