Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood R package MSIMST version 1.1 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. Software Depends: R (>= 3.4.0) Imports: MASS (>= 7.3-58.4), Rcpp (>= 1.0.12), mvtnorm (>= 1.2-4), fields (>= 15.2), parallel (>= 4.3.0), truncnorm (>= 1.0-9), Rdpack (>= 2.6) LinkingTo: Rcpp, RcppArmadillo Suggests: lattice (>= 0.21-8), HDInterval (>= 0.2.4), latex2exp (>= 0.9.6), posterior (>= 1.5.0) Qingyang Liu <rh8liuqy@gmail.com> Comprehensive R Archive Network (CRAN) Qingyang Liu [aut, cre] (ORCID: <https://orcid.org/0000-0003-3265-6330>), Debdeep Pati [aut], Dipankar Bandyopadhyay [aut] GPL (>= 3) 2024-09-16 application/tgz https://CRAN.R-project.org/package=MSIMST doi:10.32614/CRAN.package.MSIMST