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.