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Stochastic and statistical analysis of long-range dependent processes with Mathematica

A. Novikov
N. Kordzakhia
Journal / Anthology

Innovation in Mathematics: Proceedings of the Second International Mathematica Symposium
Year: 1997
Page range: 369-376

Mathematical models of stationary long-range dependent processes are more complicated then ordinary autoregressive models as they involve fractional difference equations (or, even fractional differential equations in continuous time case). The explicit representation of solutions of these equations requires special functions like hypergeometric of Gegenbauer polynomials. This paper demonstrates that Mathematica capability doing symbolic calculations makes both stochastic and statistical analysis of stationary processes with long memory easier.

*Mathematics > Probability and Statistics