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 |
| Reference manual: | RandomCoefficients.pdf |
| Vignettes: |
RandomCoefficients vignette |
| 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: RandomCoefficients_0.0.2.tgz, r-oldrel: RandomCoefficients_0.0.2.tgz |
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