llike_pacf

<p>Conditional Gaussian likelihood (good enough for sampling steps)</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

llike_pacf function

Conditional Gaussian likelihood (good enough for sampling steps) — llike_pacf

Conditional Gaussian likelihood (good enough for sampling steps)

llike_pacf: Conditional Gaussian likelihood (good enough for sampling steps)

Description

Usage

Arguments