Different post-selection inference strategies for kernel selection, as described in "kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection", Slim et al., Proceedings of Machine Learning Research, 2019, <http://proceedings.mlr.press/v97/slim19a/slim19a.pdf>. The strategies rest upon quadratic kernel association scores to measure the association between a given kernel and an outcome of interest. The inference step tests for the joint effect of the selected kernels on the outcome. A fast constrained sampling algorithm is proposed to derive empirical p-values for the test statistics.
| Version: | 1.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 1.0.1), CompQuadForm, pracma, kernlab, lmtest |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | bindata, knitr, rmarkdown, MASS, testthat |
| Published: | 2019-09-08 |
| Author: | Lotfi Slim [aut, cre], Clément Chatelain [ctb], Chloé-Agathe Azencott [ctb], Jean-Philippe Vert [ctb] |
| Maintainer: | Lotfi Slim <lotfi.slim at mines-paristech.fr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://proceedings.mlr.press/v97/slim19a.html |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | kernelPSI results |
| Reference manual: | kernelPSI.pdf |
| Vignettes: |
kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection |
| Package source: | kernelPSI_1.1.0.tar.gz |
| Windows binaries: | r-devel: kernelPSI_1.1.0.zip, r-devel-gcc8: kernelPSI_1.1.0.zip, r-release: kernelPSI_1.1.0.zip, r-oldrel: kernelPSI_1.1.0.zip |
| OS X binaries: | r-release: kernelPSI_1.1.0.tgz, r-oldrel: kernelPSI_1.1.0.tgz |
| Old sources: | kernelPSI archive |
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