runstats: Fast Computation of Running Statistics for Time Series

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: 1.0.1
Suggests: covr, testthat, ggplot2, knitr, rmarkdown, sessioninfo, rbenchmark, cowplot, spelling
Published: 2019-03-13
Author: Marta Karas ORCID iD [aut, cre], Jacek Urbanek ORCID iD [aut], John Muschelli ORCID iD [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

Downloads:

Reference manual: runstats.pdf
Vignettes: Examples of using runstats package
Package source: runstats_1.0.1.tar.gz
Windows binaries: r-devel: runstats_1.0.1.zip, r-release: runstats_1.0.1.zip, r-oldrel: runstats_1.0.1.zip
OS X binaries: r-release: runstats_1.0.1.tgz, r-oldrel: runstats_1.0.1.tgz

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