bayesianOU: Bayesian Nonlinear Ornstein-Uhlenbeck Models with Stochastic
Volatility
Fits Bayesian nonlinear Ornstein-Uhlenbeck models with cubic drift,
stochastic volatility, and Student-t innovations. The package implements
hierarchical priors for sector-specific parameters and supports parallel
MCMC sampling via 'Stan'. Model comparison is performed using Pareto
Smoothed Importance Sampling Leave-One-Out (PSIS-LOO) cross-validation
following Vehtari, Gelman, and Gabry (2017)
<doi:10.1007/s11222-016-9696-4>. Prior specifications follow recommendations
from Gelman (2006) <doi:10.1214/06-BA117A> for scale parameters.
| Version: |
0.1.3 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
stats, graphics, utils |
| Suggests: |
cmdstanr, rstan (≥ 2.21.0), loo (≥ 2.5.0), posterior, ggplot2, tidyr, openxlsx, testthat (≥ 3.0.0) |
| Published: |
2025-12-19 |
| DOI: |
10.32614/CRAN.package.bayesianOU |
| Author: |
José Mauricio Gómez Julián
 [aut, cre] |
| Maintainer: |
José Mauricio Gómez Julián <isadore.nabi at pm.me> |
| BugReports: |
https://github.com/isadorenabi/bayesianOU/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/isadorenabi/bayesianOU |
| NeedsCompilation: |
no |
| Additional_repositories: |
https://mc-stan.org/r-packages/ |
| Materials: |
README |
| CRAN checks: |
bayesianOU results |
Documentation:
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