mdDelay: Find optimal delay from a multi-dimensional dataset.

In crqa: Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis

Find optimal delay from a multi-dimensional dataset.

Description

Estimates time delay for embedding of a multi-dimensional dataset.

Usage

 mdDelay(data, nbins, maxlag, criterion, threshold) 

Arguments

data	The matrix containing all variables
nbins	The number of bins considered to estimate mutual information
maxlag	Number of lags considered
criterion	A string to indicate what delay optizes mutual information: 'firstBelow' uses the lowest delay at which the AMI function drops below the value set by the threshold parameter. 'localMin' uses the position of the first local minimum of the AMI function. The categorical state on which phi is calculated
threshold	Value to select the delay when AMI drops below it.

Value

It returns the recurrence phi-coefficient profile for state k for all delays considered

Author(s)

Sebastian Wallot, Max Planck Insitute for Empirical Aesthetics Dan Moenster, Aarhus University, Moreno I. Coco, University of East London

References

Wallot, S., and Moenster, D. (2018). Calculation of average mutual information (AMI) and false-nearest neighbors (FNN) for the estimation of embedding parameters of multidimensional time -series in Matlab. Front. Psychol. - Quantitative Psychology and Measurement

See Also

mdFnn, optimizeParam

Examples

nbins = 10; maxlag = 10; criterion = "firstBelow"; threshold = exp(-1)

data(crqa) ## load the data

handset = handmovement[1:300, ] ## take less points

mdDelay(handset, nbins, maxlag, criterion, threshold)

crqa documentation built on Nov. 27, 2023, 5:10 p.m.