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 |
| Reference manual: | HeckmanStan.html , HeckmanStan.pdf |
| Package source: | HeckmanStan_1.0.0.tar.gz |
| Windows binaries: | r-devel: HeckmanStan_1.0.0.zip, r-release: HeckmanStan_1.0.0.zip, r-oldrel: HeckmanStan_1.0.0.zip |
| macOS binaries: | r-release (arm64): HeckmanStan_1.0.0.tgz, r-oldrel (arm64): HeckmanStan_1.0.0.tgz, r-release (x86_64): HeckmanStan_1.0.0.tgz, r-oldrel (x86_64): HeckmanStan_1.0.0.tgz |
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