Package: nonlinearTseries 0.3.1

Constantino A. Garcia

nonlinearTseries: Nonlinear Time Series Analysis

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).

Authors:Constantino A. Garcia [aut, cre], Gunther Sawitzki [ctb]

nonlinearTseries_0.3.1.tar.gz
nonlinearTseries_0.3.1.tar.gz(r-4.5-noble)nonlinearTseries_0.3.1.tar.gz(r-4.4-noble)
nonlinearTseries_0.3.1.tgz(r-4.4-emscripten)nonlinearTseries_0.3.1.tgz(r-4.3-emscripten)
nonlinearTseries.pdf |nonlinearTseries.html✨
nonlinearTseries/json (API)

# Install 'nonlinearTseries' in R:
install.packages('nonlinearTseries', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/constantino-garcia/nonlineartseries/issues0 issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

5.32 score 7 stars 7 packages 1.4k downloads 5 mentions 49 exports 16 dependencies

Last updated 6 months agofrom:626dd137e3. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-linux-x86_64OKMar 23 2025
R-4.4-linux-x86_64OKMar 23 2025

Exports:buildTakenscliffordMapcontourLinescorrDimcorrMatrixdfadivergencedivTimeembeddingDimsestimateestimateEmbeddingDimFFTsurrogatefindAllNeighboursfixedMassfluctuationFunctiongaussMapgetContourLineshenonikedaMapinfDimkeenanTestlogisticMaplogRadiuslorenzmaxLyapunovmcleodLiTestmutualInformationneighbourSearchnlOrdernonlinearityTestnonLinearNoiseReductionnonLinearPredictionplotLocalScalingExppoincareMapradiusrecurrencePlotrosslerrqasampleEntropysampleEntropyFunctionsinaiMapspaceTimePlotsurrogateTestthresholdTesttimeAsymmetrytimeAsymmetry2timeLagtsayTestwindowSizes

Dependencies:clicurlgluejsonlitelatticelifecycleMatrixquadprogquantmodRcppRcppArmadillorlangtseriesTTRxtszoo

nonlinearTseries Quickstart

Rendered fromnonlinearTseries_quickstart.Rmdusingknitr::rmarkdownon Mar 23 2025.

Last update: 2021-05-12
Started: 2015-05-27

Citation

To cite package ‘nonlinearTseries’ in publications use:

Garcia C (2024). nonlinearTseries: Nonlinear Time Series Analysis. R package version 0.3.1, https://CRAN.R-project.org/package=nonlinearTseries.

Corresponding BibTeX entry: 

  @Manual{,
    title = {nonlinearTseries: Nonlinear Time Series Analysis},
    author = {Constantino A. Garcia},
    year = {2024},
    note = {R package version 0.3.1},
    url = {https://CRAN.R-project.org/package=nonlinearTseries},
  }

Readme and manuals

Help Manual

Help pageTopics
Build the Takens' vectorsbuildTakens
Clifford mapcliffordMap
Obtain the contour lines of the space time plot.contourLines
Correlation sum, correlation dimension and generalized correlation dimension (order q >1).corrDim corrMatrix.corrDim embeddingDims.corrDim estimate.corrDim nlOrder.corrDim plot.corrDim plotLocalScalingExp.corrDim radius.corrDim
Returns the correlation sums stored in the _corrDim_ objectcorrMatrix
Detrended Fluctuation Analysisdfa estimate.dfa fluctuationFunction.dfa plot.dfa windowSizes.dfa
Returns the rate of divergence of close trajectories needed for the maximum Lyapunov exponent estimation.divergence
Returns the time in which the divergence of close trajectories was computed in order to estimate the maximum Lyapunov exponent.divTime
Get the embedding dimensions used for compute a chaotic invariant.embeddingDims
Estimate several chaotic invariants using linear regressionestimate
Estimate the embedding dimensionestimateEmbeddingDim
Generate surrogate data using the Fourier transformFFTsurrogate
neighbour searchfindAllNeighbours
fixed massfixedMass
Returns the fluctuation function obtained in a DFA and represented by a _dfa_ object.fluctuationFunction
Gauss mapgaussMap
Obtain the contour lines of the space time plot.getContourLines
Henon maphenon
Ikeda mapikedaMap
Information dimensionembeddingDims.infDim estimate.infDim fixedMass.infDim infDim logRadius.infDim plot.infDim plotLocalScalingExp.infDim
Keenan's testkeenanTest
Logistic maplogisticMap
Obtain the the average log(radius) computed on the information dimension algorithm.logRadius
Lorenz systemlorenz
Maximum lyapunov exponentdivergence.maxLyapunov divTime.maxLyapunov embeddingDims.maxLyapunov estimate.maxLyapunov maxLyapunov plot.maxLyapunov
McLeod-Li testmcleodLiTest
Average Mutual Information (AMI)as.numeric.mutualInf mutualInformation plot.mutualInf [.mutualInf [[.mutualInf
neighbour searchneighbourSearch
Get the order of the nonlinear chaotic invariant.nlOrder
Nonlinearity testnonlinearityTest
Nonlinear noise reductionnonLinearNoiseReduction
Nonlinear time series predictionnonLinearPrediction
Plot local scaling exponentsplotLocalScalingExp
Poincare mappoincareMap
Get the radius of the neighborhoods used for the computations of a chaotic invariant.radius
Recurrence PlotrecurrencePlot
Rossler systemrossler
Recurrence Quantification Analysis (RQA)rqa
Sample Entropy (also known as Kolgomorov-Sinai Entropy)embeddingDims.sampleEntropy estimate.sampleEntropy nlOrder.sampleEntropy plot.sampleEntropy radius.sampleEntropy sampleEntropy sampleEntropyFunction.sampleEntropy
Returns the sample entropy function h_q(m,r) used for the computations of the sample entropy.sampleEntropyFunction
Sinai mapsinaiMap
Space Time plotcontourLines.spaceTimePlot getContourLines.spaceTimePlot plot.spaceTimePlot spaceTimePlot
Surrogate data testingsurrogateTest
Threshold nonlinearity testthresholdTest
Time Reversibility statistictimeAsymmetry
Time Reversibility statistictimeAsymmetry2
Estimate an appropiate time lag for the Takens' vectorstimeLag
Tsay's testtsayTest
Returns the window sizes used for DFA in a _dfa_ object.windowSizes