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lchemix

A Bayesian Multi-Dimensional Couple-Based Latent Risk Model

v0.1.0 · Feb 28, 2020 · GPL-3

Description

A joint latent class model where a hierarchical structure exists, with an interaction between female and male partners of a couple. A Bayesian perspective to inference and Markov chain Monte Carlo algorithms to obtain posterior estimates of model parameters. The reference paper is: Beom Seuk Hwang, Zhen Chen, Germaine M.Buck Louis, Paul S. Albert, (2018) "A Bayesian multi-dimensional couple-based latent risk model with an application to infertility". Biometrics, 75, 315-325. <doi:10.1111/biom.12972>.

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NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Weimin Zhang <zhangwm@hotmail.com>’

Found the following URLs which should use \doi (with the DOI name only):
  File ‘JLchemix.Rd’:
    https://doi.org/10.1111/biom.12972
  File ‘sampledata.Rd’:
    https://doi.org/10.1111/biom.12972
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Weimin Zhang <zhangwm@hotmail.com>’

Found the following URLs which should use \doi (with the DOI name only):
  File ‘JLchemix.Rd’:
    https://doi.org/10.1111/biom.12972
  File ‘sampledata.Rd’:
    https://doi.org/10.1111/biom.12972

Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Weimin Zhang <zhangwm@hotmail.com>’

Found the following URLs which should use \doi (with the DOI name only):
  File ‘JLchemix.Rd’:
    https://doi.org/10.1111/biom.12972
  File ‘sampledata.Rd’:
    https://doi.org/10.1111/biom.12972
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Weimin Zhang <zhangwm@hotmail.com>’

Found the following URLs which should use \doi (with the DOI name only):
  File ‘JLchemix.Rd’:
    https://doi.org/10.1111/biom.12972
  File ‘sampledata.Rd’:
    https://doi.org/10.1111/biom.12972

Dependency Network

Dependencies Reverse dependencies MCMCpack mvtnorm lchemix

Version History

new 0.1.0 Mar 10, 2026