Description Usage Arguments Value Note Author(s) References Examples
Determine significance of wavelet coherence
1 2 
nrands 
number of Monte Carlo randomizations. Default is 300. 
lag1 
vector containing the AR(1) coefficient of each time series. 
dt 
length of a time step. 
ntimesteps 
number of time steps in time series. 
pad 
pad the values will with zeros to increase the speed of the
transform. Default is 
dj 
spacing between successive scales. Default is 1/12. 
s0 
smallest scale of the wavelet. Default is 
J1 
number of scales  1. 
max.scale 
maximum scale 
mother 
type of mother wavelet function to use. Can be set to

sig.level 
significance level to compute. Default is 
quiet 
Do not display progress bar. Default is 
Returns significance matrix containing the sig.level
percentile of wavelet coherence at each time step and scale.
The Monte Carlo randomizations can be extremely slow for large datasets. For instance, 1000 randomizations of a dataset consisting of 1000 samples will take ~30 minutes on a 2.66 GHz dualcore Xeon processor.
Tarik C. Gouhier ([email protected])
Code based on WTC MATLAB package written by Aslak Grinsted.
Cazelles, B., M. Chavez, D. Berteaux, F. Menard, J. O. Vik, S. Jenouvrier, and N. C. Stenseth. 2008. Wavelet analysis of ecological time series. Oecologia 156:287304.
Grinsted, A., J. C. Moore, and S. Jevrejeva. 2004. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics 11:561566.
Torrence, C., and G. P. Compo. 1998. A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society 79:6178.
Torrence, C., and P. J. Webster. 1998. The annual cycle of persistence in the El Nino/Southern Oscillation. Quarterly Journal of the Royal Meteorological Society 124:19852004.
1 2  # Not run: wtcsig < wtc.sig(nrands, lag1 = c(d1.ar1, d2.ar1), dt,
# pad, dj, J1, s0, mother = "morlet")

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