fd.psd: Power Spectral Density Slope (PSD).

In FredHasselman/nlRtsa: nonlineaR time seRies analysis.

Description

Estimate Alpha, Hurst Exponent and Fractal Dimension through log-log slope.

Usage

## S3 method for class 'psd'
fd(y, fs = NULL, normalize = TRUE, dtrend = TRUE,
  plot = FALSE)

Arguments

y	A numeric vector or time series object.
normalize	Normalize the series (default).
plot	Return the log-log spectrum with linear fit (default).
detrend	Subtract linear trend from the series (default).

Details

Calls function SDF to estimate the scaling exponent of a timeseries based on the periodogram frequency spectrum. After detrending and normalizing the signal (if requested), SDF is called using a Tukey window (raised cosine taper).

A line is fitted on the periodogram in log-log coordinates. Two fit-ranges are used: The 25% lowest frequencies and the Hurvich-Deo estimate (HDEst).

Value

A list object containing:

• A data matrix PLAW with columns freq.norm, size and bulk.

• Estimate of scaling exponent alpha based on a fit over the lowest 25% frequencies (low25), or using the HD estimate HD.

• Estimate of the the Fractal Dimension (FD) using conversion formula's reported in Hasselman(2013).

• Information output by various functions.

Author(s)

Fred Hasselman

References

Hasselman, F. (2013). When the blind curve is finite: dimension estimation and model inference based on empirical waveforms. Frontiers in Physiology, 4, 75. http://doi.org/10.3389/fphys.2013.00075

See Also

Other FD estimators: fd.dfa, fd.sda

Examples

fd.psd(rnorm(2048), plot = TRUE)

FredHasselman/nlRtsa documentation built on May 6, 2019, 5:07 p.m.