Package: pboost 0.4.11

Zengchao Xu

pboost: Profile Boosting Framework for Parametric Models

A profile boosting framework for feature selection in parametric models. It offers a unified interface pboost() and several wrapped models, including linear model, generalized linear models, quantile regression, Cox proportional hazards model, beta regression, spatial auto-regressive models.

Authors:Zengchao Xu [aut, cre, cph]

pboost_0.4.11.tar.gz
pboost_0.4.11.zip(r-4.7)pboost_0.4.11.zip(r-4.6)pboost_0.4.11.zip(r-4.5)
pboost_0.4.11.tgz(r-4.6-any)pboost_0.4.11.tgz(r-4.5-any)
pboost_0.4.11.tar.gz(r-4.7-any)pboost_0.4.11.tar.gz(r-4.6-any)
pboost_0.4.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
pboost/json (API)
NEWS

# Install 'pboost' in R:

install.packages('pboost', repos = c('https://paradoxical-rhapsody.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/paradoxical-rhapsody/pboost/issues

On CRAN:

3.04 score 506 downloads 31 exports 61 dependencies

Last updated from:af80813c05. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	202
source / vignettes	OK	224
linux-release-x86_64	OK	197
macos-release-arm64	OK	161
macos-oldrel-arm64	OK	111
windows-devel	OK	157
windows-release	OK	160
windows-oldrel	OK	153
wasm-release	OK	132

Exports:EBIC fbetareg fcoxph fglm fglm.fit flagsarlm flm flm.fit frq frq.fit frs fsar.fit get_rho pbetareg pboost pcoxph pen_glmnet pen_ncvreg pen_rq pen_sar pggm pglm pglm.fit plagsarlm plm plm.fit prq prq.fit psar.fit sar.fit set_rook_matrix

Dependencies:backports betareg boot checkmate class classInt cli coda codetools data.table DBI deldir e1071 flexmix foreach Formula generics glmnet hqreg hrqglas insight iterators KernSmooth lattice LearnBayes lifecycle lmtest marginaleffects MASS Matrix MatrixModels modeltools multcomp mvtnorm ncvreg nlme nnet plyr proxy quantreg rbibutils Rcpp RcppArmadillo RcppEigen Rdpack rlang rqPen s2 sandwich sf shape sp SparseM spatialreg spData spdep survival TH.data units wk zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Extract Coefficients from Lasso Penalized Models	coef.penaltyglmnet
Extract Coefficients from Non-Convex Penalized Models	coef.penaltyncvreg
Extract Coefficients from Non-Convex Penalized Models	coef.penaltyrq
Extended Bayesian Information Criterion	EBIC
Forward Regression Selection for Beta Regression Models	fbetareg
Forward Regression Selection for Cox proportional hazards Model	fcoxph
Forward Regression Selection for Generalized Linear Models	fglm fglm.fit
Forward Stepwise Spatial Auto-Regressive Model	flagsarlm fsar fsar.fit
Forward Regression Selection for Linear Models.	flm flm.fit
Forward Regression Selection for Quantile Regression Models	frq frq.fit
Forward Regression Selection Framework	frs
Profile Boosting for Beta Regression	pbetareg
Profile Boosting Framework	pboost
Profile Boosting for Cox proportional hazards Model	pcoxph
Penalized Methods for Feature Selection	penalization pen_glmnet pen_ncvreg pen_rq pen_sar
Profile Boosting for Gaussian Graphical Model	pggm
Profile Boosting for Generalized Linear Models.	pglm pglm.fit
Profile Boosting for Spatial Auto-regressive Model	plagsarlm psar psar.fit
Profile Boosting for Linear Models.	plm plm.fit
Profile Boosting for Quantile Regression Models	prq prq.fit
Functions for Spatial Auto-regressive Model	BIC.sarpboost coef.sarpboost get_rho logLik.sarpboost residuals.sarpboost sar.fit sar.model set_rook_matrix