fast_ift

<p>Compute F_n^t X_n with the real-valued Fourier matrix F_n</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

fast_ift function

Compute F_n^t X_n with the real-valued Fourier matrix F_n — fast_ift

Compute F_n^t X_n with the real-valued Fourier matrix F_n

fast_ift: Compute F_n^t X_n with the real-valued Fourier matrix F_n

Description

Usage

Arguments