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]

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manual.pdf |manual.html
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.

fortran

2.74 score 37 scripts 262 downloads 3 mentions 6 exports 38 dependencies

Last updated from:b4d7c0eabf. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK132
linux-devel-x86_64OK132
source / vignettesOK174
linux-release-arm64OK140
linux-release-x86_64OK126
macos-release-arm64OK179
macos-release-x86_64OK381
macos-oldrel-arm64OK153
macos-oldrel-x86_64OK288
windows-develOK125
windows-releaseOK119
windows-oldrelOK120
wasm-releaseOK108

Exports:idmidmModelintensityshrsimulateIDMsurvIC

Dependencies:clicodetoolscpp11data.tablediagramdigestfarverfuturefuture.applyggplot2globalsgluegtableisobandKernSmoothlabelinglatticelavalifecyclelistenvMatrixmvtnormnumDerivparallellyprodlimprogressrR6RColorBrewerRcpprlangS7scalesshapeSQUAREMsurvivalvctrsviridisLitewithr