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cff-version: 1.2.0
message: 'To cite package "MSIMST" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'MSIMST: Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood'
version: '1.1'
doi: 10.32614/CRAN.package.MSIMST
abstract: 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:
- family-names: Liu
  given-names: Qingyang
  email: rh8liuqy@gmail.com
  orcid: https://orcid.org/0000-0003-3265-6330
- family-names: Pati
  given-names: Debdeep
  email: debdeep@stat.tamu.edu
- family-names: Bandyopadhyay
  given-names: Dipankar
  email: dbandyop@vcu.edu
repository: https://rh8liuqy.r-universe.dev
repository-code: https://github.com/rh8liuqy/MSIMST
commit: a1fe05ff50338adf6606c592b4dd10ea2d4993b9
url: https://github.com/rh8liuqy/MSIMST
date-released: '2024-08-16'
contact:
- family-names: Liu
  given-names: Qingyang
  email: rh8liuqy@gmail.com
  orcid: https://orcid.org/0000-0003-3265-6330