bayesianOU-package

bayesianOU

Fits Bayesian nonlinear Ornstein-Uhlenbeck models with cubic drift,
stochastic volatility (SV), and Student-t innovations. The package
implements hierarchical priors for sector-specific parameters and
supports parallel MCMC sampling via 'Stan'.

internal

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.

José Mauricio Gómez Julián

Bayesian Nonlinear Ornstein-Uhlenbeck Models with Stochastic
Volatility

bayesianOU-package function

<ul>
<li><code>fit_ou_nonlinear_tmg</code>: Fit the main OU model</li>
<li><code>extract_posterior_summary</code>: Extract posterior summaries</li>
<li><code>validate_ou_fit</code>: Validate model fit</li>
<li><code>compare_models_loo</code>: Compare models via PSIS-LOO</li>
</ul>

Main Functions

The model implements a nonlinear OU process with cubic drift:
$$dY_t = \kappa(\theta - Y_t + a_3 (Y_t - \theta)^3) dt + \sigma_t dW_t$$

Model Specification

Maintainer: José Mauricio Gómez Julián <a href="/link/isadore.nabi%40pm.me?package=bayesianOU&version=0.1.3" data-mini-rdoc="bayesianOU::isadore.nabi@pm.me">isadore.nabi@pm.me</a> (<a href="https://orcid.org/0009-0000-2412-3150">ORCID</a>)

Author

bayesianOU: Bayesian Nonlinear Ornstein-Uhlenbeck Models — bayesianOU-package

<ul>
<li><code>fit_ou_nonlinear_tmg</code>: Fit the main OU model</li>
<li><code>extract_posterior_summary</code>: Extract posterior summaries</li>
<li><code>validate_ou_fit</code>: Validate model fit</li>
<li><code>compare_models_loo</code>: Compare models via PSIS-LOO</li>
</ul>

The model implements a nonlinear OU process with cubic drift:
$$dY_t = \kappa(\theta - Y_t + a_3 (Y_t - \theta)^3) dt + \sigma_t dW_t$$

Maintainer: José Mauricio Gómez Julián <a href='mailto:isadore.nabi@pm.me'>isadore.nabi@pm.me</a> (<a href='https://orcid.org/0009-0000-2412-3150'>ORCID</a>)

bayesianOU-package: bayesianOU: Bayesian Nonlinear Ornstein-Uhlenbeck Models

Description

Arguments

Main Functions

Model Specification

Author

See Also