wclust | R Documentation |
Compute dissimilarity between multiple wavelet spectra
wclust(w.arr, quiet = FALSE)
w.arr |
|
quiet |
Do not display progress bar. |
Returns a list containing:
diss.mat |
square dissimilarity matrix |
dist.mat |
(lower triangular) distance matrix |
Tarik C. Gouhier (tarik.gouhier@gmail.com)
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.
t1 <- cbind(1:100, sin(seq(0, 10 * 2 * pi, length.out = 100)))
t2 <- cbind(1:100, sin(seq(0, 10 * 2 * pi, length.out = 100) + 0.1 * pi))
t3 <- cbind(1:100, rnorm(100)) # white noise
## Compute wavelet spectra
wt.t1 <- wt(t1)
wt.t2 <- wt(t2)
wt.t3 <- wt(t3)
## Store all wavelet spectra into array
w.arr <- array(dim = c(3, NROW(wt.t1$wave), NCOL(wt.t1$wave)))
w.arr[1, , ] <- wt.t1$wave
w.arr[2, , ] <- wt.t2$wave
w.arr[3, , ] <- wt.t3$wave
## Compute dissimilarity and distance matrices
w.arr.dis <- wclust(w.arr)
plot(hclust(w.arr.dis$dist.mat, method = "ward.D"),
sub = "", main = "", ylab = "Dissimilarity", hang = -1)
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