RandomCoefficients: Adaptive Estimation in the Linear Random Coefficients Models

We implement adaptive estimation of the joint density linear model where the coefficients - intercept and slopes - are random and independent from regressors which support is a proper subset. The estimator proposed in Gaillac and Gautier (2019) <arXiv:1905.06584> is based on Prolate Spheroidal Wave Functions which are computed efficiently in 'RandomCoefficients'. This package also provides a parallel implementation of the estimator.

Version: 0.0.2
Depends: R (≥ 3.0.0)
Imports: snowfall, stats, orthopolynom, polynom, fourierin, sfsmisc, tmvtnorm, rdetools, ks, statmod, RCEIM, robustbase, VGAM
Suggests: knitr, rmarkdown
Published: 2019-06-07
Author: Christophe Gaillac [aut, cre], Eric Gautier [aut]
Maintainer: Christophe Gaillac <christophe.gaillac at ensae.fr>
License: GPL-3
NeedsCompilation: no
CRAN checks: RandomCoefficients results

Documentation:

Reference manual: RandomCoefficients.pdf
Vignettes: RandomCoefficients vignette

Downloads:

Package source: RandomCoefficients_0.0.2.tar.gz
Windows binaries: r-devel: RandomCoefficients_0.0.2.zip, r-release: RandomCoefficients_0.0.2.zip, r-oldrel: RandomCoefficients_0.0.2.zip
macOS binaries: r-release (arm64): RandomCoefficients_0.0.2.tgz, r-release (x86_64): RandomCoefficients_0.0.2.tgz, r-oldrel: RandomCoefficients_0.0.2.tgz

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