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.
—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: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com).
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.