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]

bsplinePsd_0.6.0.tar.gz
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bsplinePsd_0.6.0.tgz(r-4.4-x86_64)bsplinePsd_0.6.0.tgz(r-4.4-arm64)bsplinePsd_0.6.0.tgz(r-4.3-x86_64)bsplinePsd_0.6.0.tgz(r-4.3-arm64)
bsplinePsd_0.6.0.tar.gz(r-4.5-noble)bsplinePsd_0.6.0.tar.gz(r-4.4-noble)
bsplinePsd_0.6.0.tgz(r-4.4-emscripten)bsplinePsd_0.6.0.tgz(r-4.3-emscripten)
bsplinePsd.pdf |bsplinePsd.html
bsplinePsd/json (API)
NEWS

# Install 'bsplinePsd' in R:
install.packages('bsplinePsd', repos = c('https://mcthedwards.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

2.70 score 1 stars 3 scripts 241 downloads 2 exports 1 dependencies

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

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-win-x86_64OKNov 13 2024
R-4.5-linux-x86_64OKNov 13 2024
R-4.4-win-x86_64OKNov 13 2024
R-4.4-mac-x86_64OKNov 13 2024
R-4.4-mac-aarch64OKNov 13 2024
R-4.3-win-x86_64OKNov 13 2024
R-4.3-mac-x86_64OKNov 13 2024
R-4.3-mac-aarch64OKNov 13 2024

Exports:dbsplinegibbs_bspline

Dependencies:Rcpp