Package: SmoothHazard 2025.07.24

SmoothHazard: Estimation of Smooth Hazard Models for Interval-Censored Data

Estimation of two-state (survival) models and irreversible illness- death models with possibly interval-censored, left-truncated and right-censored data. Proportional intensities regression models can be specified to allow for covariates effects separately for each transition. We use either a parametric approach with Weibull baseline intensities or a semi-parametric approach with M-splines approximation of baseline intensities in order to obtain smooth estimates of the hazard functions. Parameter estimates are obtained by maximum likelihood in the parametric approach and by penalized maximum likelihood in the semi-parametric approach.

Authors:Celia Touraine [aut], Thomas Alexander Gerds [aut, cre], Pierre Joly [aut], Cecile Proust-Lima [aut], Helene Jacqmin-Gadda [aut], Amadou Diakite [aut], W.D. Cody [aut], A.H. Morris [aut], B.W. Brown [aut], Robin Genuer [ctb]

SmoothHazard_2025.07.24.tar.gz
SmoothHazard_2025.07.24.zip(r-4.7-x86_64)SmoothHazard_2025.07.24.zip(r-4.7-arm64)SmoothHazard_2025.07.24.zip(r-4.6-x86_64)SmoothHazard_2025.07.24.zip(r-4.6-arm64)SmoothHazard_2025.07.24.zip(r-4.5-x86_64)
SmoothHazard_2025.07.24.tgz(r-4.6-x86_64)SmoothHazard_2025.07.24.tgz(r-4.6-arm64)SmoothHazard_2025.07.24.tgz(r-4.5-x86_64)SmoothHazard_2025.07.24.tgz(r-4.5-arm64)
SmoothHazard_2025.07.24.tar.gz(r-4.7-arm64)SmoothHazard_2025.07.24.tar.gz(r-4.7-x86_64)SmoothHazard_2025.07.24.tar.gz(r-4.6-arm64)SmoothHazard_2025.07.24.tar.gz(r-4.6-x86_64)
SmoothHazard_2025.07.24.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SmoothHazard/json (API)

# Install 'SmoothHazard' in R:
install.packages('SmoothHazard', repos = c('https://tagteam.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • Paq1000 - Paquid data set
  • testdata - Data set for survival models: right-censored and interval-censored data.

On CRAN:

Conda:

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

fortranglibc

3.26 score 1 packages 40 scripts 401 downloads 3 mentions 6 exports 38 dependencies

Last updated from:b4d7c0eabf. Checks:14 OK, 1 WARNING. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK102
linux-devel-x86_64OK146
source / vignettesOK169
linux-release-arm64OK115
linux-release-x86_64OK136
macos-release-arm64OK105
macos-release-x86_64OK175
macos-oldrel-arm64OK106
macos-oldrel-x86_64OK265
windows-devel-arm64OK239
windows-devel-x86_64OK165
windows-release-arm64WARNING243
windows-release-x86_64OK103
windows-oldrel-x86_64OK115
wasm-releaseOK88

Exports:idmidmModelintensityshrsimulateIDMsurvIC

Dependencies:clicodetoolscpp11data.tablediagramdigestfarverfuturefuture.applyggplot2globalsgluegtableisobandKernSmoothlabelinglatticelavalifecyclelistenvMatrixmvtnormnumDerivparallellyprodlimprogressrR6RColorBrewerRcpprlangS7scalesshapeSQUAREMsurvivalvctrsviridisLitewithr