Package: icenReg 2.0.16
icenReg: Regression Models for Interval Censored Data
Regression models for interval censored data. Currently supports Cox-PH, proportional odds, and accelerated failure time models. Allows for semi and fully parametric models (parametric only for accelerated failure time models) and Bayesian parametric models. Includes functions for easy visual diagnostics of model fits and imputation of censored data.
Authors:
icenReg_2.0.16.tar.gz
icenReg_2.0.16.zip(r-4.5)icenReg_2.0.16.zip(r-4.4)icenReg_2.0.16.zip(r-4.3)
icenReg_2.0.16.tgz(r-4.4-x86_64)icenReg_2.0.16.tgz(r-4.4-arm64)icenReg_2.0.16.tgz(r-4.3-x86_64)icenReg_2.0.16.tgz(r-4.3-arm64)
icenReg_2.0.16.tar.gz(r-4.5-noble)icenReg_2.0.16.tar.gz(r-4.4-noble)
icenReg_2.0.16.tgz(r-4.4-emscripten)icenReg_2.0.16.tgz(r-4.3-emscripten)
icenReg.pdf |icenReg.html✨
icenReg/json (API)
NEWS
# Install 'icenReg' in R: |
install.packages('icenReg', repos = c('https://pistacliffcho.r-universe.dev', 'https://cloud.r-project.org')) |
- IR_diabetes - Interval censored time from diabetes onset to diabetic nephronpathy
- miceData - Lung Tumor Interval Censored Data from Hoel and Walburg 1972
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:26fadac37c. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 09 2024 |
R-4.5-win-x86_64 | OK | Nov 09 2024 |
R-4.5-linux-x86_64 | OK | Nov 09 2024 |
R-4.4-win-x86_64 | OK | Nov 09 2024 |
R-4.4-mac-x86_64 | OK | Nov 09 2024 |
R-4.4-mac-aarch64 | OK | Nov 09 2024 |
R-4.3-win-x86_64 | OK | Nov 09 2024 |
R-4.3-mac-x86_64 | OK | Nov 09 2024 |
R-4.3-mac-aarch64 | OK | Nov 09 2024 |
Exports:bayesControlscs2icdiag_baselinediag_covargetFitEstsgetSCurvesic_bayesic_npic_paric_sampleic_spimputeCensir_clustBootlines.icenReg_fitmakeCtrls_icspplot.icenReg_fitsampleSurvsimCS_weibsimDC_weibsimIC_clustersimIC_weibsurvCIs
Dependencies:codacodetoolsforeachiteratorslatticeMatrixMLEcensRcppRcppEigensurvival