Package: SmoothHazard 2024.04.10

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]

SmoothHazard_2024.04.10.tar.gz
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SmoothHazard_2024.04.10.tgz(r-4.4-emscripten)SmoothHazard_2024.04.10.tgz(r-4.3-emscripten)
SmoothHazard.pdf |SmoothHazard.html
SmoothHazard/json (API)

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

Peer review:

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.

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

fortran

2.73 score 36 scripts 257 downloads 3 mentions 6 exports 22 dependencies

Last updated 8 months agofrom:7e55a8fa4a. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 07 2024
R-4.5-linux-x86_64NOTEDec 07 2024

Exports:idmidmModelintensityshrsimulateIDMsurvIC

Dependencies:clicodetoolsdata.tablediagramdigestfuturefuture.applyglobalsKernSmoothlatticelavalistenvMatrixmvtnormnumDerivparallellyprodlimprogressrRcppshapeSQUAREMsurvival