
We combine two existing estimators of the local Hurst exponent to improve both the goodness of fit and the computational speed of the algorithm. An application with simulated time series is implemented, and a Monte Carlo simulation is performed to provide evidence of the improvement.
Time series, auto-correlation, regression, etc. in statistics (GARCH), Fractional processes, including fractional Brownian motion, Gaussian processes, Statistical analysis, Statistical physics, Probability theory, Monte Carlo methods, Computational methods, Stochastic processes, Mathematical physics, Brownian motion, Gaussian processes; Statistical analysis; Statistical physics; Probability theory; Monte Carlo methods; Computational methods; Stochastic processes; Mathematical physics; Brownian motion, Computational methods for problems pertaining to statistics, Non-Markovian processes: estimation
Time series, auto-correlation, regression, etc. in statistics (GARCH), Fractional processes, including fractional Brownian motion, Gaussian processes, Statistical analysis, Statistical physics, Probability theory, Monte Carlo methods, Computational methods, Stochastic processes, Mathematical physics, Brownian motion, Gaussian processes; Statistical analysis; Statistical physics; Probability theory; Monte Carlo methods; Computational methods; Stochastic processes; Mathematical physics; Brownian motion, Computational methods for problems pertaining to statistics, Non-Markovian processes: estimation
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