R: Estimate Hurst Exponent

hurst.est {Rwave} | R Documentation

## Estimate Hurst Exponent

### Description

Estimates Hurst exponent from a wavelet transform.

### Usage

    hurst.est(wspec, range, nvoice, plot=TRUE)

### Arguments

`wspec` | wavelet spectrum (output of `tfmean`)
`range` | range of scales from which estimate the exponent.
`nvoice` | number of scales per octave of the wavelet transform.
`plot` | if set to `TRUE`, displays regression line on current plot.

### Value

complex 1D array of size sigsize.

### References

See discussions in the text of “Practical Time-Frequency Analysis”.

### See Also

`tfmean`, `wspec.pl`.

### Examples

    # 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)

[Package Rwave version 2.4-5 Index]