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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.3 |
2026-04-09 windows/windows R-4.5 | bayesianOU_0.1.3.zip |
116.7 KiB |