Package: gamboostLSS 2.1-0
Benjamin Hofner
gamboostLSS: Boosting Methods for 'GAMLSS'
Boosting models for fitting generalized additive models for location, shape and scale ('GAMLSS') to potentially high dimensional data.
Authors:
gamboostLSS_2.1-0.tar.gz
gamboostLSS_2.1-0.zip(r-4.5)gamboostLSS_2.1-0.zip(r-4.4)gamboostLSS_2.1-0.zip(r-4.3)
gamboostLSS_2.1-0.tgz(r-4.5-any)gamboostLSS_2.1-0.tgz(r-4.4-any)gamboostLSS_2.1-0.tgz(r-4.3-any)
gamboostLSS_2.1-0.tar.gz(r-4.5-noble)gamboostLSS_2.1-0.tar.gz(r-4.4-noble)
gamboostLSS_2.1-0.tgz(r-4.4-emscripten)gamboostLSS_2.1-0.tgz(r-4.3-emscripten)
gamboostLSS.pdf |gamboostLSS.html✨
gamboostLSS/json (API)
NEWS
| # Install 'gamboostLSS' in R: |
| install.packages('gamboostLSS', repos = c('https://boost-r.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/boost-r/gamboostlss/issues
boosting-algorithmsgamboostlssgamlssmachine-learningr-languagevariable-selection
Last updated 30 days agofrom:9021dc3854. Checks:6 OK, 3 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 26 2025 |
| R-4.5-win | NOTE | Mar 26 2025 |
| R-4.5-mac | NOTE | Mar 26 2025 |
| R-4.5-linux | NOTE | Mar 26 2025 |
| R-4.4-win | OK | Mar 26 2025 |
| R-4.4-mac | OK | Mar 26 2025 |
| R-4.4-linux | OK | Mar 26 2025 |
| R-4.3-win | OK | Mar 26 2025 |
| R-4.3-mac | OK | Mar 26 2025 |
Exports:as.familiesBetaLSSBetaMuBetaPhiblackboostLSScvrisk.mboostLSScvrisk.nc_mboostLSSDirichletAlphaDirichletLSSFamiliesgamboostLSSgamboostLSS_interngamlss.Familiesgamlss1parMugamlss2parMugamlss2parSigmagamlss3parMugamlss3parNugamlss3parSigmagamlss4parMugamlss4parNugamlss4parSigmagamlss4parTauGammaLSSGammaMuGammaSigmaGaussianLSSGaussianMuGaussianSigmaglmboostLSSLogLogLSSLogLogMuLogLogSigmaLogNormalLSSLogNormalMuLogNormalSigmamake.gridmboostLSSmboostLSS_fitmodel.weightsNBinomialLSSNBinomialMuNBinomialSigmaPIplot.cvriskLSSplot.gamboostLSSplot.glmboostLSSplot.nc_cvriskLSSplot.predintpredict.mboostLSSpredintselectedselected.mboostLSSselected.stabsel_mboostLSSstabsel.mboostLSSStudentTDfStudentTLSSStudentTMuStudentTSigmaWeibullLSSWeibullMuWeibullSigmaweighted.medianZINBLSSZIPoLSS
Dependencies:FormulainumlatticelibcoinMatrixmboostmvtnormnnlspartykitquadprogrpartstabssurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Boosting algorithms for GAMLSS | gamboostLSS-package |
| Include 'gamlss' families in the boosting framework of 'gamboostLSS' | as.families gamlss.Families gamlss1parMu gamlss2parMu gamlss2parSigma gamlss3parMu gamlss3parNu gamlss3parSigma gamlss4parMu gamlss4parNu gamlss4parSigma gamlss4parTau |
| Cross-Validation | cvrisk cvrisk.mboostLSS cvrisk.nc_mboostLSS make.grid plot.cvriskLSS plot.nc_cvriskLSS |
| Families for GAMLSS models | BetaLSS BetaMu BetaPhi DirichletAlpha DirichletLSS Families families GammaLSS GammaMu GammaSigma GaussianLSS GaussianMu GaussianSigma LogLogLSS LogLogMu LogLogSigma LogNormalLSS LogNormalMu LogNormalSigma NBinomialLSS NBinomialMu NBinomialSigma options stabilize_ngrad stabilize_ngradient stab_ngrad StudentTDf StudentTLSS StudentTMu StudentTSigma WeibullLSS WeibullMu WeibullSigma ZINBLSS ZIPoLSS |
| Malnutrition of Children in India (DHS, 1998-99) | india india.bnd |
| Fitting GAMLSS by Boosting | blackboostLSS gamboostLSS glmboostLSS mboostLSS mboostLSS_fit |
| Methods for mboostLSS | coef.glmboostLSS coef.mboostLSS fitted.mboostLSS model.weights model.weights.default model.weights.mboostLSS mstop.cvriskLSS mstop.mboostLSS mstop.oobag PI plot.gamboostLSS plot.glmboostLSS plot.predint predict.mboostLSS predint print.mboostLSS risk risk.mboostLSS risk.nc_mboostLSS selected selected.mboostLSS summary.mboostLSS update.mboostLSS [.mboostLSS |
| Stability Selection | selected.stabsel_mboostLSS stabsel.mboostLSS |
| Weighted Median | weighted.median |
