Package: bsplinePsd 0.6.0

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). <doi.org/10.1007/s11222-017-9796-9>.

Authors:Matthew C. Edwards [aut, cre], Renate Meyer [aut], Nelson Christensen [aut]

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bsplinePsd/json (API)
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Peer review:

Bug tracker:https://github.com/mcthedwards/bsplinepsd/issues

On CRAN:

2 exports 1 stars 0.74 score 1 dependencies 3 scripts 228 downloads

Last updated 6 years agofrom:c3a7ef1a9f. Checks:OK: 9. Indexed: yes.

Exports:dbsplinegibbs_bspline

Dependencies:Rcpp