psd
Adaptive, sine-multitaper power spectral density estimation in R
Science Score: 49.0%
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Repository
Adaptive, sine-multitaper power spectral density estimation in R
Basic Info
- Host: GitHub
- Owner: abarbour
- Language: R
- Default Branch: master
- Homepage: https://cran.r-project.org/package=psd
- Size: 118 MB
Statistics
- Stars: 9
- Watchers: 2
- Forks: 6
- Open Issues: 2
- Releases: 0
Topics
Metadata Files
README.md
psd
Adaptive, sine multitaper power spectral density estimation for R
by Andrew J Barbour, Jonathan Kennel, and Robert L Parker
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Latest News
As of version 2.0, one can calculate the multivariate PSD ("cross spectra") between two signals.
Description
This is an R package for computing univariate power spectral density estimates with little or no tuning effort. We employ sine multitapers, allowing the number to vary with frequency in order to reduce mean square error, the sum of squared bias and variance, at each point. The approximate criterion of Riedel and Sidorenko (1995) is modified to prevent runaway averaging that otherwise occurs when the curvature of the spectrum goes to zero. An iterative procedure refines the number of tapers employed at each frequency. The resultant power spectra possess significantly lower variances than those of traditional, non-adaptive estimators. The sine tapers also provide useful spectral leakage suppression. Resolution and uncertainty can be estimated from the number of degrees of freedom (twice the number of tapers).
This technique is particularly suited to long time series, because it demands only one numerical Fourier transform, and requires no costly additional computation of taper functions, like the Slepian functions. It also avoids the degradation of the low-frequency performance associated with record segmentation in Welch's method. Above all, the adaptive process relieves the user of the need to set a tuning parameter, such as time-bandwidth product or segment length, that fixes frequency resolution for the entire frequency interval; instead it provides frequency-dependent spectral resolution tailored to the shape of the spectrum itself.
psd elegantly handles
spectra with large dynamic range and mixed-bandwidth features|features
typically found in geophysical datasets.
How to Cite
Bob and Andy have a paper in Computers & Geosciences
to accompany this software (download a pdf, 1MB); it describes the theory behind
the estimation process, and how we apply it in practice.
If you find psd useful in your research, we kindly request
you cite our paper. See also:
citation("psd")
Getting Started
You can to install the package and it's dependencies
with CRAN
(from within the R environment):
install.packages("psd")
then load the package library
library(psd)
We have included a dataset to play with, namely Tohoku, which represents
recordings of high-frequency borehole strainmeter data during
teleseismic waves from the 2011 Mw 9.0 Tohoku
earthquake (original data source).
Access and inspect these data with:
data(Tohoku)
print(str(Tohoku))
The 'preseismic' data has interesting spectral features, so we subset it, and analyze the areal strain (the change in borehole diameter):
Dat <- subset(Tohoku, epoch=="preseismic")
Areal <- ts(Dat$areal)
For the purposes of improving the accuracy of the spectrum, we remove a linear trend:
Dat <- prewhiten(Areal, plot=FALSE)
Now we can calculate the adaptive PSD:
mtpsd <- pspectrum(Dat[['prew_lm']], plot=TRUE)
print(class(mtpsd))
In the previous example the plot=TRUE flag produces a comparison with a basic periodogram, but
we can also visualize the spectrum with builtin plotting methods:
plot(mtpsd, log="dB")
The spectral uncertainty can be easily calculated:
sprop <- spectral_properties(mtpsd)
with(sprop, {
plot(taper/max(taper), type="h", ylim=c(0,2), col="dark grey")
lines(stderr.chi.lower)
lines(stderr.chi.upper)
})
Installing the Development Version
Should you wish to install the development version of this software, the remotes library will be useful:
library(remotes)
remotes::install_github("abarbour/psd")
GitHub Events
Total
- Push event: 7
- Create event: 1
Last Year
- Push event: 7
- Create event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Andy Barbour | a****r@g****m | 286 |
| Andy Barbour | a****r@u****u | 109 |
| jkennel | j****l@u****a | 34 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 6
- Total pull requests: 3
- Average time to close issues: about 1 month
- Average time to close pull requests: 1 day
- Total issue authors: 4
- Total pull request authors: 1
- Average comments per issue: 2.83
- Average comments per pull request: 2.0
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- abarbour (2)
- gmgeorg (2)
- HaoLi111 (1)
- sbcalaff (1)
Pull Request Authors
- jkennel (3)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 1,267 last-month
- Total docker downloads: 43,390
- Total dependent packages: 4
- Total dependent repositories: 6
- Total versions: 11
- Total maintainers: 1
cran.r-project.org: psd
Adaptive, Sine-Multitaper Power Spectral Density and Cross Spectrum Estimation
- Homepage: https://github.com/abarbour/psd
- Documentation: http://cran.r-project.org/web/packages/psd/psd.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
-
Latest release: 2.1.2
published 10 months ago
Rankings
Maintainers (1)
Dependencies
- R >= 2.14.1 depends
- RColorBrewer * imports
- Rcpp >= 0.11.5 imports
- RSEIS * suggests
- bspec * suggests
- fftw >= 1.0.3 suggests
- formatR * suggests
- ggplot2 >= 0.9 suggests
- knitr * suggests
- multitaper * suggests
- plyr * suggests
- rbenchmark * suggests
- reshape2 * suggests
- rmarkdown * suggests
- signal * suggests
- testthat >= 2.1.0 suggests
- actions/checkout v3 composite
- r-lib/actions/check-r-package v2 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite
- r-lib/actions/setup-tinytex v2 composite
- actions/checkout v2 composite
- r-lib/actions/setup-r v1 composite
- r-lib/actions/setup-r-dependencies v1 composite