Package: penPHcure 1.0.2

Alessandro Beretta

penPHcure: Variable Selection in PH Cure Model with Time-Varying Covariates

Implementation of the semi-parametric proportional-hazards (PH) of Sy and Taylor (2000) <doi:10.1111/j.0006-341X.2000.00227.x> extended to time-varying covariates. Estimation and variable selection are based on the methodology described in Beretta and Heuchenne (2019) <doi:10.1080/02664763.2018.1554627>; confidence intervals of the parameter estimates may be computed using a bootstrap approach. Moreover, data following the PH cure model may be simulated using a method similar to Hendry (2014) <doi:10.1002/sim.5945>, where the event-times are generated on a continuous scale from a piecewise exponential distribution conditional on time-varying covariates.

Authors:Alessandro Beretta [aut, cre], Cédric Heuchenne [aut]

penPHcure_1.0.2.tar.gz
penPHcure_1.0.2.tar.gz(r-4.5-noble)penPHcure_1.0.2.tar.gz(r-4.4-noble)
penPHcure_1.0.2.tgz(r-4.4-emscripten)penPHcure_1.0.2.tgz(r-4.3-emscripten)
penPHcure.pdf |penPHcure.html✨
penPHcure/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/a-beretta/penphcure/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

1.70 score 3 scripts 128 downloads 2 exports 8 dependencies

Last updated 5 years agofrom:c0b323c358. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-linux-x86_64NOTEOct 10 2024

Exports:penPHcurepenPHcure.simulate

Dependencies:latticeMASSMatrixrbibutilsRcppRcppArmadilloRdpacksurvival