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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.

Versions across snapshots

VersionRepositoryFileSize
1.1 rolling linux/jammy R-4.5 MSIMST_1.1.tar.gz 369.9 KiB
1.1 rolling linux/noble R-4.5 MSIMST_1.1.tar.gz 372.3 KiB
1.1 rolling source/ R- MSIMST_1.1.tar.gz 706.2 KiB
1.1 latest linux/jammy R-4.5 MSIMST_1.1.tar.gz 369.9 KiB
1.1 latest linux/noble R-4.5 MSIMST_1.1.tar.gz 372.3 KiB
1.1 latest source/ R- MSIMST_1.1.tar.gz 706.2 KiB
1.1 2026-04-26 source/ R- MSIMST_1.1.tar.gz 706.2 KiB
1.1 2026-04-23 source/ R- MSIMST_1.1.tar.gz 706.2 KiB
1.1 2026-04-09 windows/windows R-4.5 MSIMST_1.1.zip 694.3 KiB
1.1 2025-04-20 source/ R- MSIMST_1.1.tar.gz 706.2 KiB

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