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DChaos  

Chaotic Time Series Analysis
View on CRAN: Click here


Download and install DChaos package within the R console
Install from CRAN:
install.packages("DChaos")

Install from Github:
library("remotes")
install_github("cran/DChaos")

Install by package version:
library("remotes")
install_version("DChaos", "0.1-7")



Attach the package and use:
library("DChaos")
Maintained by
Julio E. Sandubete
[Scholar Profile | Author Map]
First Published: 2019-04-14
Latest Update: 2023-03-29
Description:
Chaos theory has been hailed as a revolution of thoughts and attracting ever increasing attention of many scientists from diverse disciplines. Chaotic systems are nonlinear deterministic dynamic systems which can behave like an erratic and apparently random motion. A relevant field inside chaos theory and nonlinear time series analysis is the detection of a chaotic behaviour from empirical time series data. One of the main features of chaos is the well known initial value sensitivity property. Methods and techniques related to test the hypothesis of chaos try to quantify the initial value sensitive property estimating the Lyapunov exponents. The DChaos package provides different useful tools and efficient algorithms which test robustly the hypothesis of chaos based on the Lyapunov exponent in order to know if the data generating process behind time series behave chaotically or not.
How to cite:
Julio E. Sandubete (2019). DChaos: Chaotic Time Series Analysis. R package version 0.1-7, https://cran.r-project.org/web/packages/DChaos. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1-1 (2019-04-14 13:02), 0.1-2 (2019-05-29 09:30), 0.1-3 (2019-10-17 00:00), 0.1-4 (2020-05-04 23:50), 0.1-5 (2020-05-10 08:50), 0.1-6 (2021-02-10 11:40)
Other packages that cited DChaos R package
View DChaos citation profile
Other R packages that DChaos depends, imports, suggests or enhances
Complete documentation for DChaos
Functions, R codes and Examples using the DChaos R package
Some associated functions: embedding . gauss.sim . henon.sim . jacobian.net . logistic.sim . lyapunov.max . lyapunov . lyapunov.spec . netfit . rossler.sim . summary.lyapunov . w0.net . 
Some associated R codes: embedding.R . gauss.sim.R . henon.sim.R . jacobian.net.R . logistic.sim.R . lyapunov.R . lyapunov.max.R . lyapunov.spec.R . netfit.R . rossler.sim.R . summary.lyapunov.R . w0.net.R .  Full DChaos package functions and examples
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