wt.sig: Determine significance of wavelet transform

In biwavelet: Conduct univariate and bivariate wavelet analyses

Description

Determine significance of wavelet transform

Usage

wt.sig (d, dt, scale, sig.test = 0, sig.level = 0.95, dof = 2, 
        lag1 = NULL, mother = c("morlet", "paul", "dog"), 
        param = -1, sigma2 = NULL)

Arguments

d	time series in matrix format (n rows x 2 columns). The first column should contain the time steps and the second column should contain the values.
dt	length of a time step.
scale	the wavelet scale.
sig.test	type of significance test. If set to 0, use a regular χ^2 test. If set to 1, then perform a time-average test. If set to 2, then do a scale-average test.
sig.level	significance level. Default is 0.95.
dof	degrees of freedom for each point in wavelet power.
lag1	AR(1) coefficient of time series used to test for significant patterns.
mother	type of mother wavelet function to use. Can be set to morlet, dog, or paul. Default is morlet.
param	nondimensional parameter specific to the wavelet function.
sigma2	variance of time series

Value

Returns a list containing:

signif	vector containing significance level for each scale
signif	vector of red-noise spectrum for each period

Author(s)

Tarik C. Gouhier ([e-mail])

Code based on wavelet MATLAB program written by Christopher Torrence and Gibert P. Compo.

References

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

Examples

## Not run: wt.sig (d, dt, scale, sig.test, sig.level, lag1, dof=-1, 
##  mother=morlet, sigma2=1)

Example output

biwavelet 0.20.19 loaded.

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