criticalvaluesWSP {sowas}R Documentation

Estimates critical values for Wavelet spectra


This function estimates critical values for the Wavelet spectra by means of Monte Carlo simulations. Null Hypothesis is an AR1 (red noise) process fitted to the given time series.


criticalvaluesWSP(ts, s0 = 1, noctave = 5, nvoice = 10, w0 = 2*pi, swabs
= 0, tw = 0, siglevel = 0.95, nreal = 1000)


ts time series object
s0 lowest calculated scale in units of the time series
noctave number of octaves
nvoice number of voices per octave
w0 time/frequency resolution omega0
swabs length of smoothing window is 2swabs+1
tw length of smoothing window in time direction is 2*s*tw+1
siglevel significance level, e.g. 0.9, 0.95 or 0.99. siglevel might also be a vector, e.g. c(0.9,0.95) to plot more contourlines.
nreal number of realizations to estimate critical values for the corresponding significance values, default 1000


nreal might be chosen as 100 for a rough estimate of significance. However, it is for sure not suitable to reliably distinguish between 95 and 99 percent significance values. In this case, at least nreal=1000 should be chosen.


Returns a matrix of scale DEPENDENT critical values. The number of rows of the matrix corresponds to the number of chosen significance values. The number of columns equals the number of scales.



D. Maraun


D. Maraun and J. Kurths, Nonlin. Proc. Geophys. 11: 505-514, 2004

See Also




[Package sowas version 0.93 Index]