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license: MIT
title: 'bayesianOU: Bayesian Nonlinear Ornstein-Uhlenbeck Models with Stochastic Volatility'
version: 0.2.0
doi: 10.32614/CRAN.package.bayesianOU
abstract: 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) <https://doi.org/10.1007/s11222-016-9696-4>.
  Prior specifications follow recommendations from Gelman (2006) <https://doi.org/10.1214/06-BA117A>
  for scale parameters.
authors:
- family-names: Gómez Julián
  given-names: José Mauricio
  email: isadore.nabi@pm.me
  orcid: https://orcid.org/0009-0000-2412-3150
repository: https://isadorenabi.r-universe.dev
repository-code: https://github.com/IsadoreNabi/bayesianOU
commit: e9d52c0d1fc55d0eaca9de15c33dd401e4fc23c1
url: https://github.com/IsadoreNabi/bayesianOU
date-released: '2026-07-31'
contact:
- family-names: Gómez Julián
  given-names: José Mauricio
  email: isadore.nabi@pm.me
  orcid: https://orcid.org/0009-0000-2412-3150