seewave (version 1.1)

corenv: Cross-correlation between two time wave envelopes

Description

This function tests the similarity between two time wave envelopes by returning their maximal correlation and the time shift related to it.

Usage

corenv(wave1, wave2, f, smooth = 20, plot = TRUE, plotval = TRUE,
method = "spearman", col = "black", colval = "red",
cexval = 1, fontval = 1, xlab = "Time (s)",
ylab = "Coefficient of correlation (r)", ...)

Arguments

wave1

data describing a first time wave.

wave2

data describing a second time wave.

f

sampling frequency of wave1 and wave2.

smooth

smoothes the envelopes of wave1 and wave2 by averaging the number of points selected.

plot

logical, if TRUE plots r values against frequency shift (by default TRUE).

plotval

logical, if TRUE adds to the plot maximum r value and frequency offset (by default TRUE).

method

a character string indicating which correlation coefficient is to be computed ("pearson", "spearman", or "kendall") (see cor).

col

colour of r values.

colval

colour of r max and frequency offset values.

cexval

character size of r max and frequency offset values.

fontval

font of r max and frequency offset values.

xlab

title of the frequency axis.

ylab

title of the r axis.

...

other plot graphical parameters.

Value

• If plot is FALSE, corenv returns a list containing four components:
• r
  the successive correlation values between x and y.
• rmax
  the maximum correlation value between x and y.
• p
  the p value corresponding to rmax.
• f
  the time offset corresponding to rmax.

Details

Successive correlations between the envelopes of wave1 and wave2 are computed when regularly sliding forward and backward wave2 along wave1. The maximal correlation is obtained at a particular shift (time offset). This shift may be positive or negative. The higher smooth is set up, the faster will be the computation but less precise the results will be. The corresponding p value, obtained with cor.test, is plotted. Inverting wave1 and wave2 may give slight different results.

See Also

spec,covspectro, cor, cor.test.

Examples

data(orni)
# cross-correlation between two echemes of a cicada song
wave1<-cutw(orni,f=22050,from=0.3,to=0.4,plot=FALSE)
wave2<-cutw(orni,f=22050,from=0.58,to=0.68,plot=FALSE)
corenv(wave1,wave2,f=22050,type="l",ylim=c(-0.7,1.1))