Package: gamlss.foreach 1.1-6

Mikis Stasinopoulos

gamlss.foreach: Parallel Computations for Distributional Regression

Computational intensive calculations for Generalized Additive Models for Location Scale and Shape, <doi:10.1111/j.1467-9876.2005.00510.x>.

Authors:Mikis Stasinopoulos [aut, cre, cph], Bob Rigby [aut], Fernanda De Bastiani [aut]

gamlss.foreach_1.1-6.tar.gz
gamlss.foreach_1.1-6.tar.gz(r-4.5-noble)gamlss.foreach_1.1-6.tar.gz(r-4.4-noble)
gamlss.foreach_1.1-6.tgz(r-4.4-emscripten)gamlss.foreach_1.1-6.tgz(r-4.3-emscripten)
gamlss.foreach.pdf |gamlss.foreach.html
gamlss.foreach/json (API)

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

Peer review:

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

2.56 score 1 packages 12 scripts 253 downloads 113 mentions 12 exports 16 dependencies

Last updated 2 years agofrom:f301e551ad. Checks:OK: 1 NOTE: 1. Indexed: yes.

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

Exports:BayesianBootcentiles.bootfitPCRfitRollinggamlss.pcgamlss.pcrgetSVDNonParametricBootpcpcrwhich.Data.Corrwhich.yX.Corr

Dependencies:codetoolsdoParallelforeachgamlssgamlss.datagamlss.distglmnetiteratorslatticeMASSMatrixnlmeRcppRcppEigenshapesurvival

Readme and manuals

Help Manual

Help pageTopics
Computational Intensive Functions within GAMLSSgamlss.foreach-package gamlss.foreach
Non parametric and Bayesian Bootstrapping for GAMLSS modelsBayesianBoot NonParametricBoot
Bootstrapping centiles curves estimated using GAMLSScentiles.boot plot.centiles.boot print.centiles.boot summary.centiles.boot
Function to fit simple Principal Component Regression.fitPCR
Function to Fit Rolling Regression in gamlssfitRolling
Methods for PCR objectscoef.PCR fitted.PCR plot.PCR predict.PCR summary.PCR vcov.PCR
Functions to Fit Principal Component Regression in GAMLSSgamlss.pc gamlss.pcr getSVD pc pcr
Detecting Hight Pair-Wise Correlations in Datawhich.Data.Corr which.yX.Corr