surrogates: Generate phase-randomized surrogate series as in Ebisuzaki...

surrogatesR Documentation

Generate phase-randomized surrogate series as in Ebisuzaki (1997)

Description

Generate phase-randomized surrogate series as in Ebisuzaki (1997).

Usage

surrogates(dat,nsim=1,preserveMean=T,std=T,genplot=T,verbose=T)

Arguments

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)

Details

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.

References

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/

Examples

# 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)

astrochron documentation built on Aug. 26, 2023, 5:07 p.m.