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-oldrel (arm64): RandomCoefficients_0.0.2.tgz, r-release (x86_64): RandomCoefficients_0.0.2.tgz, r-oldrel (x86_64): RandomCoefficients_0.0.2.tgz

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