wdist: Compute dissimilarity between two wavelet spectra

In biwavelet: Conduct univariate and bivariate wavelet analyses

Description

Compute dissimilarity between two wavelet spectra

Usage

wdist (wt1, wt2, cutoff = 0.99)

Arguments

wt1	power, wave or rsq matrix from biwavelet object generated by wt, xwt, or wtc.
wt2	power, wave or rsq matrix from biwavelet object generated by wt, xwt, or wtc.
cutoff	cutoff value used to compute dissimilarity. Only orthogonal axes that contribute more than 1-cutoff to the total covariance between the two wavelet spectra will be used to compute their dissimilarity. Default is 0.99.

Value

Returns wavelet dissimilarity.

Author(s)

Tarik C. Gouhier ([e-mail])

References

Rouyer, T., J. M. Fromentin, F. Menard, B. Cazelles, K. Briand, R. Pianet, B. Planque, and N. C. Stenseth. 2008. Complex interplays among population dynamics, environmental forcing, and exploitation in fisheries. Proceedings of the National Academy of Sciences 105:5420-5425.

Rouyer, T., J. M. Fromentin, N. C. Stenseth, and B. Cazelles. 2008. Analysing multiple time series and extending significance testing in wavelet analysis. Marine Ecology Progress Series 359:11-23.

Examples

t1=cbind(1:100, sin(seq(from=0, to=10*2*pi, length.out=100)))
t2=cbind(1:100, sin(seq(from=0, to=10*2*pi, length.out=100)+0.1*pi))
## Compute wavelet spectra
wt.t1=wt(t1)
wt.t2=wt(t2)
## Compute dissimilarity
wdist(wt.t1$wave, wt.t2$wave)

Example output

biwavelet 0.20.17 loaded.
[1] 0.04286993

biwavelet documentation built on May 2, 2019, 5:10 p.m.