psd: Adaptive, Sine-Multitaper Power Spectral Density Estimation

Produces power spectral density estimates through iterative refinement of the optimal number of sine-tapers at each frequency. This optimization procedure is based on the method of Riedel and Sidorenko (1995), which minimizes the Mean Square Error (sum of variance and bias) at each frequency, but modified for computational stability.

Version: 1.2.0
Depends: R (≥ 2.14.1)
Imports: Rcpp (≥ 0.11.5), RColorBrewer, signal, zoo
LinkingTo: Rcpp, RcppArmadillo
Suggests: bspec, fftw (≥ 1.0.3), ggplot2 (≥ 0.9), knitr, multitaper, plyr, RSEIS, rbenchmark, reshape2, testthat
Published: 2019-03-20
Author: Andrew J. Barbour [aut, cre] (ORCID iD), Robert L. Parker [cre], Jonathan Kennel [ctb]
Maintainer: Andrew J. Barbour <andy.barbour at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:, Barbour and Parker (2014):, Riedel and Sidorenko (1995):
NeedsCompilation: yes
Citation: psd citation info
Materials: README NEWS
In views: TimeSeries
CRAN checks: psd results


Reference manual: psd.pdf
Vignettes: DFT benchmarks: fft vs FFT
Normalization of power spectral density estimates
An overview of psd
Package source: psd_1.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: psd_1.0-1.tgz, r-oldrel: psd_1.0-1.tgz
Old sources: psd archive

Reverse dependencies:

Reverse suggests: kitagawa, multitaper


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