biwavelet (version 0.20.22)

wtc.sig: Determine significance of wavelet coherence

Description

Determine significance of wavelet coherence

Usage

wtc.sig(
  nrands = 300,
  lag1,
  dt,
  ntimesteps,
  pad = TRUE,
  dj = 1/12,
  s0,
  J1,
  max.scale = NULL,
  mother = "morlet",
  sig.level = 0.95,
  quiet = FALSE
)

Value

Returns significance matrix containing the sig.level

percentile of wavelet coherence at each time step and scale.

Arguments

nrands

Number of Monte Carlo randomizations.

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.

dj

Spacing between successive scales.

s0

Smallest scale of the wavelet.

J1

Number of scales - 1.

max.scale

Maximum scale.

mother

Type of mother wavelet function to use. Can be set to morlet, dog, or paul. Significance testing is only available for morlet wavelet.

sig.level

Significance level to compute.

quiet

Do not display progress bar.

Author

Tarik C. Gouhier ([e-mail])

Code based on WTC MATLAB package written by Aslak Grinsted.

References

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 156:287-304.

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 11:561-566.

Torrence, C., and G. P. Compo. 1998. A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society 79:61-78.

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 124:1985-2004.

Examples

# Not run: wtcsig <- wtc.sig(nrands, lag1 = c(d1.ar1, d2.ar1), dt,
#                            pad, dj, J1, s0, mother = "morlet")