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)", type = "l",...)Sample object generated loading a wav file
with loadSample (package Sample object generated loading a wav file
with loadSample (package wave1 and wave1 (in Hz).
Does not need to be specified if wave1 and/or wave2 are/is (a)
Sample object(s).wave1 and wave2
by floating average.TRUE plots r values against frequency shift
(by default TRUE).TRUE adds to the plot maximum r value
and frequency offset (by default TRUE).cor).plot is TRUE, type of plot that should be drawn.
See plot for details (by default "l" for lines).plot graphical parameters.plot is FALSE, corenv returns a list containing four
components:x and y.x and y.rmax.rmax.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.spec,covspectro,
cor, cor.test.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,ylim=c(-0.7,1.1))Run the code above in your browser using DataLab