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nonlinearTseries (version 0.3.1)

Nonlinear Time Series Analysis

Description

Functions for nonlinear time series analysis. This package permits the computation of the most-used nonlinear statistics/algorithms including generalized correlation dimension, information dimension, largest Lyapunov exponent, sample entropy and Recurrence Quantification Analysis (RQA), among others. Basic routines for surrogate data testing are also included. Part of this work was based on the book "Nonlinear time series analysis" by Holger Kantz and Thomas Schreiber (ISBN: 9780521529020).

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install.packages('nonlinearTseries')

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1,555

Version

0.3.1

License

GPL-3

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Repository

https://github.com/constantino-garcia/nonlinearTseries

Maintainer

Constantino A. Garcia

Last Published

September 23rd, 2024

Functions in nonlinearTseries (0.3.1)

getContourLines

Obtain the contour lines of the space time plot.

Returns the correlation sums stored in the corrDim object

fluctuationFunction

Returns the fluctuation function obtained in a DFA and represented by a dfa object.

Estimate several chaotic invariants using linear regression

Maximum lyapunov exponent

estimateEmbeddingDim

Estimate the embedding dimension

Sample Entropy (also known as Kolgomorov-Sinai Entropy)

Build the Takens' vectors

sampleEntropyFunction

Returns the sample entropy function \(h_q(m,r)\) used for the computations of the sample entropy.

Obtain the the average log(radius) computed on the information dimension algorithm.

Space Time plot

plotLocalScalingExp

Plot local scaling exponents

Estimate an appropiate time lag for the Takens' vectors

Recurrence Quantification Analysis (RQA)

findAllNeighbours

neighbour search

Returns the window sizes used for DFA in a dfa object.

Get the order of the nonlinear chaotic invariant.

mutualInformation

Average Mutual Information (AMI)

neighbourSearch

neighbour search

nonLinearNoiseReduction

Nonlinear noise reduction

nonlinearityTest

Nonlinearity test

nonLinearPrediction

Nonlinear time series prediction

Time Reversibility statistic

Recurrence Plot

Time Reversibility statistic

Surrogate data testing

Get the radius of the neighborhoods used for the computations of a chaotic invariant.

Threshold nonlinearity test

Detrended Fluctuation Analysis

Get the embedding dimensions used for compute a chaotic invariant.

Generate surrogate data using the Fourier transform

Correlation sum, correlation dimension and generalized correlation dimension (order q >1).

Obtain the contour lines of the space time plot.

Returns the time in which the divergence of close trajectories was computed in order to estimate the maximum Lyapunov exponent.

Returns the rate of divergence of close trajectories needed for the maximum Lyapunov exponent estimation.

Information dimension