A comment on “Measuring fractality” by Stadnitski (2012)

نویسنده

  • Maarten L. Wijnants
چکیده

In a recent publication Stadnitski (2012) presented an overview of methods to estimate fractal scaling in time series, outlined as an accessible tutorial1. The publication was set-up as a comparison between monofractal and ARFIMA methods, and promotes ARFIMA to distinguish between spurious and genuine 1/f noise, shedding light on “the problem that the log–log power spectrum of short-memory ARMA (p, q) processes can resemble the spectrum of 1/f noise.” Stadnitski proposes an analytic strategy that consists of fitting 18 models to any time series. Nine of the models are ARMA (p, q) models, with p and q varying from 0 to 2, that do not contain long-range correlations. The remaining ARFIMA (p, d, q) models add to the ARMA models a fractional integration parameter d. As laid-out by the author, given a genuine fractal series, ARFIMA models should present a better fit than ARMA counterparts. Based on this logic, Stadnitski (2012) evaluates one simple reaction time (SRT) series, and concludes it is not a genuine fractal signal. This conclusion is intriguing, because it was previously argued that SRT series typically present genuine 1/f scaling (Van Orden et al., 2003; Wagenmakers et al., 2004). In this commentary, iteratively refined spectral surrogates (Schreiber and Schmitz, 1996) were generated from the

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عنوان ژورنال:

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2014