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:Hao Helen Zhang [aut, cph], Chen-Yen Lin [aut, cph], Isaac Ray [cre, ctb]

cosso_2.1-2.tar.gz
cosso_2.1-2.tar.gz(r-4.5-noble)cosso_2.1-2.tar.gz(r-4.4-noble)
cosso_2.1-2.tgz(r-4.4-emscripten)cosso_2.1-2.tgz(r-4.3-emscripten)
cosso.pdf |cosso.html
cosso/json (API)
NEWS

# Install 'cosso' in R:
install.packages('cosso', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • BUPA - BUPA Liver Disorder Data
  • ozone - Ozone pollution data in Los Angels, 1976
  • veteran - Veterans' Administration Lung Cancer study

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.23 score 1 stars 17 scripts 223 downloads 48 exports 13 dependencies

Last updated 2 years agofrom:081b3ba559. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 21 2024
R-4.5-linuxOKDec 21 2024

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