Extensions of Rosenblatt's results on the asymptotic behavior of prediction error variance for deterministic stationary sequences
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2020-11-17
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Mamikon Ginovyan, Nikolay Babayan, Murad Taqqu. "Extensions of Rosenblatt's results on the asymptotic behavior of prediction error variance for deterministic stationary sequences."
Abstract
One of the main problem in prediction theory of discrete-time second-order stationary processes
X(t) is to describe the asymptotic behavior of the best linear mean squared prediction error in
predicting X(0) given X(t); −n ≤ t ≤ −1, as n goes to infinity. This behavior depends on the
regularity (deterministic or non-deterministic) of the process X(t). In his seminal paper "Some
purely deterministic processes" (J. of Math. and Mech., 6(6), 801-810, 1957), M. Rosenblatt
has described the asymptotic behavior of the prediction error for deterministic processes in the
following two cases: (a) the spectral density f of X(t) is continuous and vanishes on an interval,
(b) the spectral density f has a very high order contact with zero. He showed that in the case
(a) the prediction error behaves exponentially, while in the case (b), it behaves like a power as
n ⟶ ∞. In this paper, using an approach different from the one applied in Rosenblatt's paper,
we describe extensions of Rosenblatt's results to broader classes of spectral densities. Examples
illustrate the obtained results.