surrogates | R Documentation |
Generate phase-randomized surrogate series as in Ebisuzaki (1997).
surrogates(dat,nsim=1,preserveMean=T,std=T,genplot=T,verbose=T)
dat |
Data series with one or two columns. If two columns, first should be location (e.g., depth), second column should be data value. |
nsim |
Number of phase-randomized surrogate series to generate. |
preserveMean |
Should surrogate series have the same mean value as data series? (T or F) |
std |
Standardize results to guarantee equivalent variance as data series? (T or F) |
genplot |
Generate summary plots? Only applies if nsim=1. (T or F) |
verbose |
Verbose output? (T or F) |
This function will generate phase-randomized surrogate series as in Ebisuzaki (1997). It is an R-translation of the Matlab code by V. Moron (see link below), with modifications and additional features.
W. Ebisuzaki, 1997, A Method to Estimate the Statistical Significance of a Correlation When the Data Are Serially Correlated: Journal of Climate, v. 10, p. 2147-2153.
Matlab code by V. Moron: http://www.mathworks.com/matlabcentral/fileexchange/10881-weaclim/content/ebisuzaki.m
Original C-code by W. Ebisuzaki: http://www.ftp.cpc.ncep.noaa.gov/wd51we/random_phase/
# generate example series with 3 precession terms and noise
ex <- cycles(start=0,end=500,noisevar=.0004,dt=5)
# generate phase-randomized surrogates
ran_ex <- surrogates(ex,nsim=1)
# compare periodograms of data and surrogates
res1 <- periodogram(ex,padfac=0,output=1,genplot=FALSE)
res2 <- periodogram(ran_ex,padfac=0,output=1,genplot=FALSE)
pl(2)
plot(ex,type="l",main="black=original; red=surrogate")
lines(ran_ex,col="red",lty=4)
plot(res1[,1],res1[,2],type="l",lwd=2,main="black=original; red=surrogate",
xlab="frequency",ylab="amplitude")
lines(res2[,1],res2[,2],col="red",lwd=2,lty=4)
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