bsplinePsd: Bayesian Nonparametric Spectral Density Estimation Using B-Spline Priors

Implementation of a Metropolis-within-Gibbs MCMC algorithm to flexibly estimate the spectral density of a stationary time series. The algorithm updates a nonparametric B-spline prior using the Whittle likelihood to produce pseudo-posterior samples and is based on the work presented by Edwards, Meyer, and Christensen (2017) <arXiv:1707.04878>.

Version: 0.1.0
Imports: Rcpp (≥ 0.12.5), splines (≥ 3.2.3)
LinkingTo: Rcpp
Published: 2017-07-18
Author: Matthew C. Edwards [aut, cre], Renate Meyer [aut], Nelson Christensen [aut]
Maintainer: Matthew C. Edwards <matt.edwards at>
License: GPL (≥ 3)
NeedsCompilation: yes
CRAN checks: bsplinePsd results


Reference manual: bsplinePsd.pdf
Package source: bsplinePsd_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: bsplinePsd_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: bsplinePsd_0.1.0.tgz


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