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r_test / packages / r-bsplinepsd

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>.

Type Size Name Uploaded Downloads Labels
conda 127.1 kB | linux-64/r-bsplinepsd-0.6.0-r36h29659fb_0.tar.bz2  5 years and 5 months ago 0 main
conda 124.7 kB | osx-64/r-bsplinepsd-0.6.0-r36h466af19_0.tar.bz2  5 years and 5 months ago 0 main
conda 133.2 kB | win-64/r-bsplinepsd-0.6.0-r36h796a38f_0.tar.bz2  5 years and 5 months ago 0 main

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