wincrqa: Windowed Recurrence Measures

Description

A recurrence plot is computed in overlapping windows of a certain size for a number of delays smaller than the size of the window; and measures of it extracted.

Usage

wincrqa(ts1, ts2, windowstep, windowsize, delay, embed, 
radius, rescale, normalize, mindiagline, minvertline, tw, whiteline, 
recpt, side, method, metric, datatype, trend)

Value

It returns a matrix where the rows are the different windows explored, and the columns are the recurrence measures observed in that particular window. Refer to crqa for the values returned.

Arguments

ts1: First time-series
ts2: Second time-series
windowstep: Interval by which the window is moved.
windowsize: The size of the window
delay: The delay unit by which the series are lagged.
embed: The number of embedding dimension for phase-reconstruction, i.e., the lag intervals.
radius: A threshold, cut-off, constant used to decide whether two points are recurrent or not.
rescale: Rescale the distance matrix; if rescale = 0 (do nothing); if rescale = 1 (mean distance of entire matrix); if rescale = 2 (maximum distance of entire matrix). if rescale = 3 (minimum distance of entire matrix). if rescale = 4 (euclidean distance of entire matrix).
normalize: Normalize the time-series; if normalize = 0 (do nothing); if normalize = 1 (Unit interval); if normalize = 2 (z-score).
mindiagline: A minimum diagonal length of recurrent points. Usually set to 2, as it takes a minimum of two points to define any line.
minvertline: A minimum vertical length of recurrent points.
tw: The Theiler window parameter
whiteline: A logical flag to calculate (TRUE) or not (FALSE) empty vertical lines.
recpt: A logical flag indicating whether measures of cross-recurrence are calculated directly from a recurrent plot (TRUE) or not (FALSE).
side: A string indicating whether recurrence measures should be calculated in the 'upper' triangle of the RP 'lower' triangle of the matrix, or 'both'. LOC is automatically excluded for 'upper' and 'lower'.
method: A string to indicate the type of recurrence analysis to peform. There are three options: rqa (autorecurrence); crqa(cross-recurrence); mdcrqa(multidimensional recurrence). Default value is crqa
metric: A string to indicate the type of distance metric used, default is euclidean but see help rdist() to list all other possible metrics.
datatype: a string (continuous or categorical) to indicate whether the nature of the data type
trend: a boolean (TRUE or FALSE) to indicate whether the TREND should be computed of the system

Author

Moreno I. Coco (moreno.cocoi@gmail.com) Alexandra Paxton alexandra.paxton@uconn.edu

Examples

Run this code


data(crqa) 

listener = eyemovement$listener[1:200]
narrator = eyemovement$narrator[1:200]

# NB, the parameters for windowsize and windowstep are large to allow
# faster running time, please set them carefully in your analysis. 

delay = 1; embed = 1; rescale = 0; radius = 0.001;
normalize = 0; mindiagline = 2; minvertline = 2;
tw = 0; whiteline = FALSE; recpt = FALSE; side = "both"
method = 'crqa'; metric = 'euclidean';  
datatype = "continuous"; 
windowsize =  100; windowstep = 50
trend = FALSE

ans = wincrqa(listener, narrator, windowstep, windowsize, delay, embed,
                    radius, rescale, normalize, mindiagline, minvertline,
                    tw, whiteline, recpt, side, method, metric, 
                    datatype, trend)

## other recurrence measures are available in ans
profile = as.numeric(ans$RR) 

plot(profile, type = 'l')