Abstract—An algorithm is proposed that allows to estimate the self-similarity parameter of a fractal k-dimensional stochastic process. Our technique greatly improves the processing times of a distribution-based estimator, that – introduced years ago – efficiently worked only in the one-dimensional distribution case.
Index Terms—Algorithm, estimator, fractional Brownian motion, self-similar processes.
The authors are with the Department of Economics and Law, University of Cassino, (FR), Italy (e-mail: sbianchi@eco.unicas.it, palazzo@eco.unicas.it, a.pantanella@eco.unicas.it, pianese@unicas.it).
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Cite: S. Bianchi, A. M. Palazzo, A. Pantanella, and A. Pianese, "Self-Similarity Parameter Estimation for K-Dimensional Processes,"
International Journal of Computer Theory and Engineering vol. 5, no. 2, pp. 302-306, 2013.
