Abstract-In many applied problems it is required to construct a mathematical model of the dependence of output variables on input variables of the stochastic object. To solve this problem, both parametric and nonparametric approaches are used. Each of these approaches has advantages and disadvantages. In the paper, we consider combined algorithms for the identification and prediction of stochastic objects using jointly nonparametric and parametric estimates of regression.
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