Bayesian Regression Models for Interval-censored Data in R

Abstract:

The package icenReg provides classic survival regression models for interval-censored data. We present an update to the package that extends the parametric models into the Bayesian framework. Core additions include functionality to define the regression model with the standard regression syntax while providing a custom prior function. Several other utility functions are presented that allow for simplified examination of the posterior distribution.

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Author

Affiliation

Clifford Anderson-Bergman

 

Published

Oct. 23, 2017

Received

Aug 5, 2017

DOI

10.32614/RJ-2017-050

Volume

Pages

9/2

487 - 498

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2017-050.zip

CRAN packages used

icenReg, foreach, doParallel, coda, Rcpp, RcppEigen

CRAN Task Views implied by cited packages

HighPerformanceComputing, NumericalMathematics, Bayesian, gR, Survival

Footnotes

    Reuse

    Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

    Citation

    For attribution, please cite this work as

    Anderson-Bergman, "The R Journal: Bayesian Regression Models for Interval-censored Data in R", The R Journal, 2017

    BibTeX citation

    @article{RJ-2017-050,
      author = {Anderson-Bergman, Clifford},
      title = {The R Journal: Bayesian Regression Models for Interval-censored Data in R},
      journal = {The R Journal},
      year = {2017},
      note = {https://doi.org/10.32614/RJ-2017-050},
      doi = {10.32614/RJ-2017-050},
      volume = {9},
      issue = {2},
      issn = {2073-4859},
      pages = {487-498}
    }