Package: cosso 2.1-2
Isaac Ray
cosso: Fit Regularized Nonparametric Regression Models Using COSSO Penalty
The COSSO regularization method automatically estimates and selects important function components by a soft-thresholding penalty in the context of smoothing spline ANOVA models. Implemented models include mean regression, quantile regression, logistic regression and the Cox regression models.
Authors:
cosso_2.1-2.tar.gz
cosso_2.1-2.tar.gz(r-4.7-any)cosso_2.1-2.tar.gz(r-4.6-any)
cosso_2.1-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cosso/json (API)
| # Install 'cosso' in R: |
| install.packages('cosso', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:081b3ba559. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 148 | ||
| source / vignettes | OK | 171 | ||
| linux-release-x86_64 | OK | 157 | ||
| wasm-release | OK | 110 |
Exports:ACV.lambdabigGramcossocosso.Binomialcosso.Coxcosso.Cox.Parallelcosso.Cox.Sequentialcosso.Gaussiancosso.qrcosso.qr.Parallelcosso.qr.Sequentialcvlam.Gaussiancvlam.logisticcvsplitIDgarrote.Coxgarrote.Logisticgarrote.Logistic.GHgarrote.qrgenKgenK.catgradient.Hessian.Cgradient.Hessian.ThetakqrMy_solveMy_solve.QPPartialLikplot.cossopredict.cossorescalerhoRiskSetSSANOVAwtSSANOVAwt.BinomialSSANOVAwt.CoxSSANOVAwt.GaussianSSANOVAwt.qrssplinesspline.Binomialsspline.Coxtune.cossotune.cosso.Binomialtune.cosso.Coxtune.cosso.Gaussiantwostep.Binomialtwostep.Coxtwostep.Gaussiantwostep.qrwsGram
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixquadprogRcppRcppEigenRglpkshapeslamsurvival
