HeckmanStan: Heckman Selection Models Based on Bayesian Analysis (original) (raw)

Implements Heckman selection models using a Bayesian approach via 'Stan' and compares the performance of normal, Student’s t, and contaminated normal distributions in addressing complexities and selection bias (Heeju Lim, Victor E. Lachos, and Victor H. Lachos, Bayesian analysis of flexible Heckman selection models using Hamiltonian Monte Carlo, 2025, under submission).

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: rstan (≥ 2.26.23), mvtnorm (≥ 1.2-3), loo, stats
Published: 2025-05-06
DOI: 10.32614/CRAN.package.HeckmanStan
Author: Heeju Lim [aut, cre], Victor E. Lachos [aut], Victor H. Lachos [aut]
Maintainer: Heeju Lim <heeju.lim at uconn.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: HeckmanStan results

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