Package: MSIMST 1.1

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.zip(r-4.7)MSIMST_1.1.zip(r-4.6)MSIMST_1.1.zip(r-4.5)
MSIMST_1.1.tgz(r-4.6-x86_64)MSIMST_1.1.tgz(r-4.6-arm64)MSIMST_1.1.tgz(r-4.5-x86_64)MSIMST_1.1.tgz(r-4.5-arm64)
MSIMST_1.1.tar.gz(r-4.7-arm64)MSIMST_1.1.tar.gz(r-4.7-x86_64)MSIMST_1.1.tar.gz(r-4.6-arm64)MSIMST_1.1.tar.gz(r-4.6-x86_64)
MSIMST_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MSIMST/json (API)
NEWS

# Install 'MSIMST' in R:
install.packages('MSIMST', repos = c('https://rh8liuqy.r-universe.dev', '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

4.00 score 2 stars 147 downloads 6 exports 13 dependencies

Last updated from:a1fe05ff50. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK148
source / vignettesOK180
linux-release-arm64OK155
linux-release-x86_64OK131
macos-release-arm64OK150
macos-release-x86_64OK240
macos-oldrel-arm64OK266
macos-oldrel-x86_64OK358
windows-develOK154
windows-releaseOK155
windows-oldrelOK159
wasm-releaseOK102

Exports:Gibbs_SamplerphiX_creg_simulation1reg_simulation2reg_simulation3WFPBB

Dependencies:dotCall64fieldsmapsMASSmvtnormrbibutilsRColorBrewerRcppRcppArmadilloRdpackspamtruncnormviridisLite

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 May 31 2026.

Last update: 2024-09-16
Started: 2024-08-07