Improved moment scaling estimation for multifractal signals

2018

A fundamental problem in the analysis of multifractal processes is to estimate the scaling exponent K(q) of moments of different order q from data. Conventional estimators use the empirical moments μ^[subscript r][superscript q]=⟨ | ε[subscript r](τ)|[superscript q]⟩ of wavelet coefficients ε[subscript r](τ), where τ is location and r is resolution. For stationary measures one usually considers "wavelets of order 0" (averages), whereas for functions with multifractal increments one must use wavelets of order at least 1. One obtains K^(q) as the slope of log(μ^[subscript r][superscript q]) against log(r) over a range of r. Negative moments are sensitive to measurement noise and quantization.…