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 in Edwards, M.C., Meyer, R. and Christensen, N., Statistics and Computing (2018). <>.

Package details

AuthorMatthew C. Edwards [aut, cre], Renate Meyer [aut], Nelson Christensen [aut]
MaintainerMatthew C. Edwards <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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bsplinePsd documentation built on May 2, 2019, 5:56 a.m.