Package: tseriesChaos 0.1-13.1
tseriesChaos: Analysis of Nonlinear Time Series
Routines for the analysis of nonlinear time series. This work is largely inspired by the TISEAN project, by Rainer Hegger, Holger Kantz and Thomas Schreiber: <http://www.mpipks-dresden.mpg.de/~tisean/>.
Authors:
tseriesChaos_0.1-13.1.tar.gz
tseriesChaos_0.1-13.1.zip(r-4.7-x86_64)tseriesChaos_0.1-13.1.zip(r-4.7-arm64)tseriesChaos_0.1-13.1.zip(r-4.6-x86_64)tseriesChaos_0.1-13.1.zip(r-4.6-arm64)tseriesChaos_0.1-13.1.zip(r-4.5-x86_64)
tseriesChaos_0.1-13.1.tgz(r-4.6-x86_64)tseriesChaos_0.1-13.1.tgz(r-4.6-arm64)tseriesChaos_0.1-13.1.tgz(r-4.5-x86_64)tseriesChaos_0.1-13.1.tgz(r-4.5-arm64)
tseriesChaos_0.1-13.1.tar.gz(r-4.7-arm64)tseriesChaos_0.1-13.1.tar.gz(r-4.7-x86_64)tseriesChaos_0.1-13.1.tar.gz(r-4.6-arm64)tseriesChaos_0.1-13.1.tar.gz(r-4.6-x86_64)
tseriesChaos_0.1-13.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tseriesChaos/json (API)
| # Install 'tseriesChaos' in R: |
| install.packages('tseriesChaos', repos = c('https://antoniofabio.r-universe.dev', 'https://cloud.r-project.org')) |
- lorenz.ts - Lorenz simulated time series, without noise
- rossler.ts - Roessler simulated time series, without noise
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:fc60db785c. Checks:15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 73 | ||
| linux-devel-x86_64 | OK | 101 | ||
| source / vignettes | OK | 125 | ||
| linux-release-arm64 | OK | 119 | ||
| linux-release-x86_64 | OK | 99 | ||
| macos-release-arm64 | OK | 97 | ||
| macos-release-x86_64 | OK | 292 | ||
| macos-oldrel-arm64 | OK | 103 | ||
| macos-oldrel-x86_64 | OK | 292 | ||
| windows-devel-arm64 | OK | 349 | ||
| windows-devel-x86_64 | OK | 103 | ||
| windows-release-arm64 | OK | 338 | ||
| windows-release-x86_64 | OK | 75 | ||
| windows-oldrel-x86_64 | OK | 76 | ||
| wasm-release | OK | 87 |
Exports:C2d2duffing.systembeddfalse.nearestlorenz.systlyaplyap_kmutualplot.amiplot.d2plot.false.nearestprint.d2print.false.nearestrecurrrossler.systsim.contstplot
Dependencies:deSolve
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sample correlation integral | C2 |
| Sample correlation integral (at multiple length scales) | d2 |
| Duffing oscillator | duffing.syst |
| Embedding of a time series | embedd |
| Method of false nearest neighbours | false.nearest |
| Lorenz system | lorenz.syst |
| Lorenz simulated time series, without noise | lorenz.ts |
| Tools to evaluate the maximal Lyapunov exponent of a dynamic system | lyap lyap_k |
| Average Mutual Information | mutual |
| Plotting average mutual information index | plot.ami |
| Plotting sample correlation integrals | plot.d2 |
| Plotting false nearest neighbours results | plot.false.nearest |
| Printing sample correlation integrals | print.d2 |
| Printing false nearest neighbours results | print.false.nearest |
| Recurrence plot | recurr |
| Roessler system of equations | rossler.syst |
| Roessler simulated time series, without noise | rossler.ts |
| Simulates a continuous dynamic system | sim.cont |
| Space-time separation plot | stplot |