Nonparametric semirecursive identification in a wide sense of strong mixing processes

Nonparametric Algorithms of Identification and Prediction in the ARX-Models

“…Let the function ψ be bounded, the distribution density of t ε on 1 R be nonnegative with 3 0 1 Eε = and 4 1 Eε < ∞ . In this case, the process (1) is the geometric Markov chain with the strong mixing coefficient [3][4][5] …”

Mean-Square Convergence of Recursive Kernel Estimators of Non-Homogeneous Poisson Process Intensity Function and its Derivative

“…The recursive kernel estimators of the density function was introduced first by Wolverton and Wagner [20] and by Yamato independently [21] and examined thoroughly in [22]. The recursive kernel estimators of functionals of a multidimensional density function for strong mixing observations were studied in [23].…”