gibbs_nuisance

<p>Gibbs sampler for corrected parametric likelihood + Bernstein-Dirichlet mixture,
including possibility of using time series as mere nuisance parameter</p>

internal

Implementations of a Bayesian parametric (autoregressive), a Bayesian nonparametric (Whittle likelihood with Bernstein-Dirichlet prior) and a Bayesian semiparametric (autoregressive likelihood with Bernstein-Dirichlet correction) procedure are provided. The work is based on the corrected parametric likelihood by C. Kirch et al (2017) <arXiv:1701.04846>. It was supported by DFG grant KI 1443/3-1.

Alexander Meier

beyondWhittle

Bayesian Spectral Inference for Stationary Time Series

Claudia Kirch

Matthew C. Edwards

Renate Meyer

gibbs_nuisance function

Gibbs sampler for corrected parametric likelihood + Bernstein-Dirichlet mixture,
including possibility of using time series as mere nuisance parameter — gibbs_nuisance

Gibbs sampler for corrected parametric likelihood + Bernstein-Dirichlet mixture,
including possibility of using time series as mere nuisance parameter

gibbs_nuisance: Gibbs sampler for corrected parametric likelihood + Bernstein-Dirichlet mixture, including possibility of using time series as mere nuisance parameter

Description

Usage

Arguments