beyondWhittle: Bayesian Spectral Inference for Stationary Time Series

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.

Version: 1.0
Imports: ltsa (≥ 1.4.6), Rcpp (≥ 0.12.5), MASS
LinkingTo: Rcpp
Published: 2018-07-16
Author: Alexander Meier [aut, cre], Claudia Kirch [aut], Matthew C. Edwards [aut], Renate Meyer [aut]
Maintainer: Alexander Meier <alexander.meier at>
License: GPL (≥ 3)
NeedsCompilation: yes
CRAN checks: beyondWhittle results


Reference manual: beyondWhittle.pdf
Package source: beyondWhittle_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: beyondWhittle_1.0.tgz, r-oldrel: beyondWhittle_1.0.tgz
Old sources: beyondWhittle archive


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