windowdrp: Window Cross-Recurrence Profile

Description

Cross-recurrence is calculated in overlapping windows of a specified size for a number of delays smaller than the size of the window. In every window, the recurrence value for the different delays is calculated. A mean is then taken across the delays to obtain a recurrence value in that particular window.

Usage

windowdrp(x, y, step, windowsize, lagwidth, datatype, radius)

Arguments

First time-series

Second time-series

step

Interval by which the window is moved.

windowsize

The size of the window

lagwidth

The number of delays to be considered

datatype

A string indicating whether the time-series is 'numeric' or 'categorical'

radius

For numeric time-series, the cutoff distance to accept or reject two-points as recurrent

Value

It returns a list of arguments where:

profile

Time-course cross-recurrence profile

maxrec

Maximal recurrence observed along the time-series

maxlag

The point in time where maximal recurrence is observed

References

Boker, S. M., Rotondo, J. L., Xu, M., & King, K. (2002). Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series. Psychological Methods, 7(3), 338.

Examples

Run this code

# NOT RUN {
data(crqa)

par = list(type = 1, step =  20, windowsize =  50, lagwidth = 40,
  method = "window", datatype = "categorical", thrshd = 8)

ans = runcrqa(RDts1, RDts2, par)

print(ans)

profile = ans$profile; maxrec = ans$maxrec; maxlag = ans$maxlag

# }