MSIMST: The 'MSIMST' package.

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

The 'MSIMST' package.

Description

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.

Author(s)

Maintainer: Qingyang Liu [e-mail] (ORCID)

Authors:

• Debdeep Pati [e-mail]

• Dipankar Bandyopadhyay [e-mail]

See Also

Useful links:

• https://github.com/rh8liuqy/MSIMST

MSIMST documentation built on Sept. 16, 2024, 9:06 a.m.