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.
- Version0.6.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release10/18/2018
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Team
Matthew C. Edwards
MaintainerShow author detailsRenate Meyer
Show author detailsRolesAuthorNelson Christensen
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