Package: survivalMPL 0.2-4

survivalMPL: Penalised Maximum Likelihood for Survival Analysis Models

Estimate the regression coefficients and the baseline hazard of proportional hazard Cox models with left, right or interval censored survival data using maximum penalised likelihood. A 'non-parametric' smooth estimate of the baseline hazard function is provided.

Authors:Dominique-Laurent Couturier [aut, cre], Jun Ma [aut], Stephane Heritier [aut], Maurizio Manuguerra [aut], Serigne Lo [aut]

survivalMPL_0.2-4.tar.gz
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manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
survivalMPL/json (API)

# Install 'survivalMPL' in R:
install.packages('survivalMPL', repos = c('https://ptuc-stats.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • bcos2 - Breast Cosmesis Data

On CRAN:

Conda:

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

1.00 score 1 stars 6 scripts 361 downloads 12 exports 4 dependencies

Last updated from:932d09b663. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK134
source / vignettesOK136
linux-release-x86_64OK125
macos-release-arm64OK119
macos-oldrel-arm64OK104
windows-develOK81
windows-releaseOK110
windows-oldrelOK88
wasm-releaseOK112

Exports:coef.coxph_mplcoef.summary.coxph_mplcoxph_mplcoxph_mpl.controlplot.coxph_mplplot.predict.coxph_mplplot.residuals.coxph_mplpredict.coxph_mplprint.coxph_mplprint.summary.coxph_mplresiduals.coxph_mplsummary.coxph_mpl

Dependencies:latticeMASSMatrixsurvival

Readme and manuals

Help Manual

Help pageTopics
Penalised Maximum Likelihood for Survival Analysis ModelssurvivalMPL-package survivalMPL
Breast Cosmesis Databcos2
Extract coefficients of a coxph_mpl Object or of its 'summary'coef.coxph_mpl coef.summary.coxph_mpl
Fit Cox Proportional Hazards Regression Model Via MPLcoxph_mpl print.coxph_mpl
Ancillary arguments for controling coxph_mpl fitscoxph_mpl.control
MPL Proportional Hazards Regression Objectcoxph_mpl.object
Plot a coxph_mpl Objectplot.coxph_mpl
Predictions for a Cox modelplot.predict.coxph_mpl predict.coxph_mpl
Residuals for a Cox modelplot.residuals.coxph_mpl residuals.coxph_mpl
Summarise a coxph_mpl Objectprint.summary.coxph_mpl summary.coxph_mpl