Package: liftLRD 1.0-9
Matt Nunes
liftLRD: Wavelet Lifting Estimators of the Hurst Exponent for Regularly and Irregularly Sampled Time Series
Implementations of Hurst exponent estimators based on the relationship between wavelet lifting scales and wavelet energy of Knight et al (2017) <doi:10.1007/s11222-016-9698-2>.
Authors:
liftLRD_1.0-9.tar.gz
liftLRD_1.0-9.tar.gz(r-4.7-any)liftLRD_1.0-9.tar.gz(r-4.6-any)
liftLRD_1.0-9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
liftLRD/json (API)
| # Install 'liftLRD' in R: |
| install.packages('liftLRD', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:d7c237c3bc. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 106 | ||
| source / vignettes | OK | 156 | ||
| linux-release-x86_64 | OK | 107 | ||
| wasm-release | OK | 96 |
Exports:artificial.levelsbootciHfrombetaidjliftHurstmad2mean2meanjmeanmomedj
Dependencies:adliftEbayesThreshMASSnltwavethresh
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Wavelet lifting estimators of the Hurst exponent for regularly and irregularly sampled time series | liftLRD-package liftLRD |
| artificial.levels | artificial.levels |
| bootstrap confidence interval calculation | bootci |
| Compute Hurst exponent from wavelet scale - energy regression slope | Hfrombeta |
| Functions to perform summary calculations of wavelet scales and energies. | idj mad2 mean2 meanj meanmo medj |
| Performs (non-decimated) lifting based estimation of the Hurst exponent | liftHurst |