Package: BCA1SG 0.1.0

Wang Yudong

BCA1SG: Block Coordinate Ascent with One-Step Generalized Rosen Algorithm

Implementing the Block Coordinate Ascent with One-Step Generalized Rosen (BCA1SG) algorithm on the semiparametric models for panel count data, interval-censored survival data, and degradation data. A comprehensive description of the BCA1SG algorithm can be found in Wang et al. (2020) <https://github.com/yudongstat/BCA1SG/blob/master/BCA1SG.pdf>. For details of the semiparametric models for panel count data, interval-censored survival data, and degradation data, please see Wellner and Zhang (2007) <doi:10.1214/009053607000000181>, Huang and Wellner (1997) <ISBN:978-0-387-94992-5>, and Wang and Xu (2010) <doi:10.1198/TECH.2009.08197>, respectively.

Authors:Wang Yudong, Ye Zhisheng, and Cao Hongyuan

BCA1SG_0.1.0.tar.gz
BCA1SG_0.1.0.tar.gz(r-4.5-noble)BCA1SG_0.1.0.tar.gz(r-4.4-noble)
BCA1SG_0.1.0.tgz(r-4.4-emscripten)BCA1SG_0.1.0.tgz(r-4.3-emscripten)
BCA1SG.pdf |BCA1SG.html✨
BCA1SG/json (API)

# Install 'BCA1SG' in R:
install.packages('BCA1SG', repos = 'https://cloud.r-project.org')
Datasets:
  • adapt_duser - A data set adapted from the data set "duser" in the package "FHtest"
  • adapt_skiTum - A data set adapted from the data set "skiTum" in the package "spef"
  • liner - The marine engine cylinder liner data from Giorgio et al.

On CRAN:

Conda:

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

1.70 score 188 downloads 3 exports 3 dependencies

Last updated 5 years agofrom:c0ebe21d81. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 30 2025
R-4.5-linuxOKMar 30 2025
R-4.4-linuxOKMar 30 2025

Exports:BCA1SG_degradationBCA1SG_interval_censorBCA1SG_NHPP

Dependencies:latticelogOfGammaMatrix

Citation

To cite package ‘BCA1SG’ in publications use:

Yudong W, Zhisheng Y, Hongyuan C (2019). BCA1SG: Block Coordinate Ascent with One-Step Generalized Rosen Algorithm. R package version 0.1.0, https://CRAN.R-project.org/package=BCA1SG.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {BCA1SG: Block Coordinate Ascent with One-Step Generalized
      Rosen Algorithm},
    author = {Wang Yudong and Ye Zhisheng and Cao Hongyuan},
    year = {2019},
    note = {R package version 0.1.0},
    url = {https://CRAN.R-project.org/package=BCA1SG},
  }

Readme and manuals

BCA1SG: Block Coordinate Ascent with One-Step GR

Goal

BCA1SG is an R package implementing the block coordinate ascent with one-step Generalized Rosen (BCA1SG) algorithm on the semiparametric models for panel count data, interval-censored survival data, and degradation data.

Details

  • A comprehensive description of the BCA1SG algorithm can be found in Wang et al. (2020).
  • For panel count data, we focus on the semiparametric nonhomogeneous Poisson process model in Wellner and Zhang (2007).
  • For interval-censored survival data, we focus on the semiparametric proportional hazard model in Section 4 of Huang and Wellner (1997).
  • For degradation data, we focus on the semiparametric random-effects inverse Gaussian process model in Section 3 of Wang and Xu (2010).

References

Wang Y., Ye, Z.-S., and Cao, H.(2020). On Computation of Semi-Parametric Maximum Likelihood Estimators with Shape Constraints. Submitted.

Wellner J.A. and Zhang Y.(2007). Two Likelihood-Based Semiparametric Estimation Methods for Panel Count Data with Covariates. The Annals of Statistics, 35(5), 2106-2142.

Huang J. and Wellner, J.A.(1997). Interval-Censored Survival Data: A Review of Recent Progress. Proceedings of the Fifth Seattle Symposium in Biostatistics, 123-169.

Wang X. and Xu, D.(2010). An Inverse Gaussian Process Model for Degradation Data. Technometrics, 52(2), 188-197.