Provides methods for fast computation of running sample statistics for time series. These include: (1) mean, (2) standard deviation, and (3) variance over a fixed-length window of time-series, (4) correlation, (5) covariance, and (6) Euclidean distance (L2 norm) between short-time pattern and time-series. Implemented methods utilize Convolution Theorem to compute convolutions via Fast Fourier Transform (FFT).
Version: | 1.1.0 |
Imports: | fftwtools |
Suggests: | covr, testthat, ggplot2, knitr, rmarkdown, sessioninfo, rbenchmark, cowplot, spelling |
Published: | 2019-11-14 |
Author: | Marta Karas [aut, cre], Jacek Urbanek [aut], John Muschelli [ctb], Lacey Etzkorn [ctb] |
Maintainer: | Marta Karas <marta.karass at gmail.com> |
BugReports: | https://github.com/martakarass/runstats/issues |
License: | GPL-3 |
URL: | https://github.com/martakarass/runstats |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
In views: | TimeSeries |
CRAN checks: | runstats results |
Reference manual: | runstats.pdf |
Vignettes: |
Examples of using runstats package |
Package source: | runstats_1.1.0.tar.gz |
Windows binaries: | r-devel: runstats_1.1.0.zip, r-release: runstats_1.1.0.zip, r-oldrel: runstats_1.1.0.zip |
macOS binaries: | r-release: runstats_1.1.0.tgz, r-oldrel: runstats_1.1.0.tgz |
Old sources: | runstats archive |
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