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 Bayesian parametric, nonparametric and semiparametric procedures for univariate and multivariate time series. The package is based on the methods presented in C. Kirch et al (2018) <doi:10.1214/18-BA1126> and A. Meier (2018) <https://opendata.uni-halle.de//handle/1981185920/13470>. 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