bsplinePsd: Bayesian Nonparametric Spectral Density Estimation Using B-Spline Priors
Version 0.1.0

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) .

Package details

AuthorMatthew C. Edwards [aut, cre], Renate Meyer [aut], Nelson Christensen [aut]
Date of publication2017-07-18 09:16:27 UTC
MaintainerMatthew C. Edwards <[email protected]>
LicenseGPL (>= 3)
Version0.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bsplinePsd")

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bsplinePsd documentation built on July 18, 2017, 5:02 p.m.