rqa: Recurrence Quantification Analysis (RQA)

Description Usage Arguments Value Author(s) References Examples

View source: R/RQA.R

Description

The Recurrence Quantification Analysis (RQA) is an advanced technique for the nonlinear analysis that allows to quantify the number and duration of the recurrences in the phase space.

Usage

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rqa(takens = NULL, time.series = NULL, embedding.dim = 2, time.lag = 1,
  radius, lmin = 2, vmin = 2, distanceToBorder = 2, save.RM = TRUE,
  do.plot = FALSE, ...)

Arguments

takens

Instead of specifying the time.series, the embedding.dim and the time.lag, the user may specify directly the Takens' vectors.

time.series

The original time series from which the phase-space reconstruction is performed.

embedding.dim

Integer denoting the dimension in which we shall embed the time.series.

time.lag

Integer denoting the number of time steps that will be use to construct the Takens' vectors.

radius

Maximum distance between two phase-space points to be considered a recurrence.

lmin

Minimal length of a diagonal line to be considered in the RQA. Default lmin = 2.

vmin

Minimal length of a vertical line to be considered in the RQA. Default vmin = 2.

distanceToBorder

In order to avoid border effects, the distanceToBorder points near the border of the recurrence matrix are ignored when computing the RQA parameters. Default, distanceToBorder = 2.

save.RM

Logical value. If TRUE, the recurrence matrix is stored as a sparse matrix. Note that computing the recurrences in matrix form can be computationally expensive.

do.plot

Logical. If TRUE, the recurrence plot is shown. However, plotting the recurrence matrix is computationally expensive. Use with caution.

...

Additional plotting parameters.

Value

A rqa object that consist of a list with the most important RQA parameters:

Author(s)

Constantino A. Garcia and Gunther Sawitzki

References

Zbilut, J. P. and C. L. Webber. Recurrence quantification analysis. Wiley Encyclopedia of Biomedical Engineering (2006).

Examples

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## Not run: 
rossler.ts =  rossler(time=seq(0, 10, by = 0.01),do.plot=FALSE)$x
rqa.analysis=rqa(time.series = rossler.ts, embedding.dim=2, time.lag=1,
               radius=1.2,lmin=2,do.plot=FALSE,distanceToBorder=2)
plot(rqa.analysis)

## End(Not run)

Example output

Loading required package: Matrix
Loading required package: rgl
Loading required package: tseries
Loading required package: TSA
Loading required package: leaps
Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-17. For overview type 'help("mgcv-package")'.

Attaching package: 'TSA'

The following objects are masked from 'package:stats':

    acf, arima

The following object is masked from 'package:utils':

    tar

Loading required package: Rcpp

Attaching package: 'nonlinearTseries'

The following object is masked from 'package:grDevices':

    contourLines

Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 

nonlinearTseries documentation built on May 29, 2017, 8:53 p.m.