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:
vse4ts_1.0.0.tar.gz
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vse4ts.pdf |vse4ts.html✨
vse4ts/json (API)
NEWS
# 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
Last updated 4 months agofrom:4147657761. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 21 2024 |
R-4.5-win | OK | Nov 21 2024 |
R-4.5-linux | OK | Nov 21 2024 |
R-4.4-win | OK | Nov 21 2024 |
R-4.4-mac | OK | Nov 21 2024 |
R-4.3-win | OK | Nov 21 2024 |
R-4.3-mac | OK | Nov 21 2024 |
Exports:SLmemory.testvseWnoise.test
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Testing Long Memory in Time Series | SLmemory.test |
Calculate the Variance Scale Exponent of a Time Series | vse |
Testing White Noise in Time Series | Wnoise.test |