Package: SmoothHazard 2025.07.24

Thomas Alexander Gerds

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]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SmoothHazard/json (API)

# Install 'SmoothHazard' in R:
install.packages('SmoothHazard', repos = c('https://cran.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 379 downloads 3 mentions 6 exports 38 dependencies

Last updated from:b4d7c0eabf. Checks:9 OK, 1 WARNING. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK108
linux-devel-x86_64OK133
source / vignettesOK188
linux-release-arm64OK145
linux-release-x86_64OK136
windows-devel-arm64OK218
windows-devel-x86_64OK153
windows-release-arm64WARNING324
windows-release-x86_64OK101
wasm-releaseOK114

Exports:idmidmModelintensityshrsimulateIDMsurvIC

Dependencies:clicodetoolscpp11data.tablediagramdigestfarverfuturefuture.applyggplot2globalsgluegtableisobandKernSmoothlabelinglatticelavalifecyclelistenvMatrixmvtnormnumDerivparallellyprodlimprogressrR6RColorBrewerRcpprlangS7scalesshapeSQUAREMsurvivalvctrsviridisLitewithr