Related Experiment Video
Updated: Jun 27, 2026

Blast Quantification Using Hopkinson Pressure Bars
Published on: July 5, 2016
A blind method for the estimation of the Hurst exponent in time series: theory and application
Federico Esposti1, Manuela Ferrario, Maria Gabriella Signorini
1Dipartimento di Bioingegneria, Politecnico di Milano, p.zza Leonardo da Vinci, 20133 Milano, Italy. federico.esposti@polimi.it
Abstract:
Nowadays many methods for the estimation of self-similarity (Hurst coefficient, H) in time series are available. Most of them, even if very effective, need some a priori information to be applied. We analyzed the eight most used methods for H estimation (working both in time and in frequency). We tested these methods on data generated with four kinds of time series models (fBm and fGn generated iteratively with Feder algorithm, 1f(alpha), and the fractional autoregressive integrated moving-average) in the range 0.1
Related Concept Videos
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Exponential Fourier series
Euler's identity...
Routh-Hurwitz Criterion I
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
Kaplan-Meier Approach
Exponential and Sinusoidal Signals
