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MSIMST

The goal of MSIMST is to provide a Bayesian monotonic single-index mixed-effect model incorporating a multivariate skew-t likelihood with survey weights adjustments. This package includes a simulation program and the associated Gibbs sampler. The single-index function is modeled as a monotonic increasing function, with a tailored Gaussian process prior to ensure accurate estimation. Random effects are assumed to follow the canonical skew-t distribution, while residuals are modeled using the multivariate Student-t distribution. Additionally, the package provides Bayesian adjustment for survey weight information.

Installation

You can install the development version of MSIMST like so:

devtools::install_github(repo = "https://github.com/rh8liuqy/MSIMST")

Vignette

Users can access the vignette:

library(MSIMST)
vignette("MSIMST_vignette",package = "MSIMST")

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Version

Install

install.packages('MSIMST')

Monthly Downloads

126

Version

1.1

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Maintainer

Qingyang Liu

Last Published

September 16th, 2024

Functions in MSIMST (1.1)

WFPBB

Weighted Finite Population Bayesian Bootstrap
phiX_c

The Function to Calculate the phiX Matrix for Estimating Single-Index Function
reg_simulation3

The Function for the Simulation Study with the Variable Selection and Survey Weights
Gibbs_Sampler

The Associated Gibbs Sampler
MSIMST

The 'MSIMST' package.
reg_simulation1

The Function for the Simulation Study without the Variable Selection
reg_simulation2

The Function for the Simulation Study with the Variable Selection