Description Usage Arguments Value References See Also Examples
Estimates Hurst exponent from a wavelet transform.
1 |
wspec |
wavelet spectrum (output of |
range |
range of scales from which estimate the exponent. |
nvoice |
number of scales per octave of the wavelet transform. |
plot |
if set to |
complex 1D array of size sigsize.
See discussions in the text of “Practical Time-Frequency Analysis”.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # White Noise Hurst Exponent: The plots on the top row of Figure 6.8
# were produced by the folling S-commands. These make use of the two
# functions Hurst.est (estimation of Hurst exponent from CWT) and
# wspec.pl (display wavelet spectrum).
# Compare the periodogram and the wavelet spectral estimate.
wnoise <- rnorm(8192)
plot.ts(wnoise)
spwnoise <- fft(wnoise)
spwnoise <- Mod(spwnoise)
spwnoise <- spwnoise*spwnoise
plot(spwnoise[1:4096], log="xy", type="l")
lswnoise <- lsfit(log10(1:4096), log10(spwnoise[1:4096]))
abline(lswnoise$coef)
cwtwnoise <- DOG(wnoise, 10, 5, 1, plot=FALSE)
mcwtwnoise <- Mod(cwtwnoise)
mcwtwnoise <- mcwtwnoise*mcwtwnoise
wspwnoise <- tfmean(mcwtwnoise, plot=FALSE)
wspec.pl(wspwnoise, 5)
hurst.est(wspwnoise, 1:50, 5)
|
Intercept X
7.0844452 -0.4845543
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