Shannon entropy estimation for linear processes
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In this paper, we estimate the Shannon entropy S(f) = -[ log (f(x))] of a one-sided linear process with probability density function f(x). We employ the integral estimator S_n(f), which utilizes the standard kernel density estimator f_n(x) of f(x). We show that S_n (f) converges to S(f) almost surely and in Ł^2 under reasonable conditions.
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