Package: vse4ts 1.0.0

vse4ts: Identify Memory Patterns in Time Series Using Variance Scale Exponent

Methods for calculating the variance scale exponent to identify memory patterns in time series data. Includes tests for white noise, short memory, and long memory. See Fu, H. et al. (2018) <doi:10.1016/j.physa.2018.06.092>.

Authors:Mengyang Zheng [aut, cre], Hui Fu [aut]

vse4ts_1.0.0.tar.gz
vse4ts_1.0.0.zip(r-4.7-any)vse4ts_1.0.0.zip(r-4.6-any)vse4ts_1.0.0.zip(r-4.5-any)
vse4ts_1.0.0.tgz(r-4.6-any)vse4ts_1.0.0.tgz(r-4.5-any)
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vse4ts_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
vse4ts/json (API)

# Install 'vse4ts' in R:
install.packages('vse4ts', repos = c('https://z-my-cn.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/z-my-cn/vse4ts/issues

Pkgdown/docs site:https://z-my-cn.github.io

On CRAN:

Conda:

3.00 score 2 stars 3 scripts 190 downloads 3 exports 0 dependencies

Last updated from:4147657761. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK98
source / vignettesOK141
linux-releaseOK79
macos-releaseOK149
macos-oldrelOK113
windows-develOK53
windows-releaseOK57
windows-oldrelOK56
wasm-releaseOK83

Exports:SLmemory.testvseWnoise.test

Dependencies: