Bayesian Nonlinear Ornstein-Uhlenbeck Models with Stochastic Volatility R package bayesianOU version 0.2.0 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. Software Depends: R (>= 4.1.0) Imports: stats, graphics, utils, parallel Suggests: cmdstanr, rstan (>= 2.21.0), loo (>= 2.5.0), posterior, ggplot2, tidyr, openxlsx, knitr, rmarkdown, testthat (>= 3.0.0) José Mauricio Gómez Julián <isadore.nabi@pm.me> Comprehensive R Archive Network (CRAN) José Mauricio Gómez Julián [aut, cre] (ORCID: <https://orcid.org/0009-0000-2412-3150>) MIT + file LICENSE (https://CRAN.R-project.org/package=bayesianOU/LICENSE) 2026-06-18 application/tgz https://CRAN.R-project.org/package=bayesianOU doi:10.32614/CRAN.package.bayesianOU