Package: MSIMST 1.1

Qingyang Liu

MSIMST: Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood

Incorporates a Bayesian monotonic single-index mixed-effect model with a multivariate skew-t likelihood, specifically designed to handle survey weights adjustments. Features include a simulation program and an associated Gibbs sampler for model estimation. The single-index function is constrained to be monotonic increasing, utilizing a customized Gaussian process prior for precise estimation. The model assumes random effects follow a canonical skew-t distribution, while residuals are represented by a multivariate Student-t distribution. Offers robust Bayesian adjustments to integrate survey weight information effectively.

Authors:Qingyang Liu [aut, cre], Debdeep Pati [aut], Dipankar Bandyopadhyay [aut]

MSIMST_1.1.tar.gz
MSIMST_1.1.tar.gz(r-4.5-noble)MSIMST_1.1.tar.gz(r-4.4-noble)
MSIMST_1.1.tgz(r-4.4-emscripten)MSIMST_1.1.tgz(r-4.3-emscripten)
MSIMST.pdf |MSIMST.html✨
MSIMST/json (API)
NEWS

# Install 'MSIMST' in R:
install.packages('MSIMST', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/rh8liuqy/msimst/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

2.70 score 1 stars 153 downloads 6 exports 12 dependencies

Last updated 6 months agofrom:74634f06d5. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 16 2025
R-4.5-linux-x86_64OKMar 16 2025
R-4.4-linux-x86_64OKMar 16 2025

Exports:Gibbs_SamplerphiX_creg_simulation1reg_simulation2reg_simulation3WFPBB

Dependencies:dotCall64fieldsmapsMASSmvtnormrbibutilsRcppRcppArmadilloRdpackspamtruncnormviridisLite

Robust Statistical Modeling for Quantifying Periodontal Disease: A Single Index Mixed-Effects Approach with Skewed Random Effects and Heavy-Tailed Residuals

Rendered fromMSIMST_vignette.Rnwusingutils::Sweaveon Mar 16 2025.

Last update: 2024-09-17
Started: 2024-09-17

Citation

To cite package ‘MSIMST’ in publications use:

Liu Q, Pati D, Bandyopadhyay D (2024). MSIMST: Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood. R package version 1.1, https://CRAN.R-project.org/package=MSIMST.

Corresponding BibTeX entry: 

  @Manual{,
    title = {MSIMST: Bayesian Monotonic Single-Index Regression Model
      with the Skew-T Likelihood},
    author = {Qingyang Liu and Debdeep Pati and Dipankar
      Bandyopadhyay},
    year = {2024},
    note = {R package version 1.1},
    url = {https://CRAN.R-project.org/package=MSIMST},
  }