SEQUENTIAL PROCEDURE FOR NONPARAMETRIC ESTIMATION OF STOCHASTIC DE-PENDENCE | Zendy

А. V. Lapko | Zendy; В. А. Лапко | Zendy

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SEQUENTIAL PROCEDURE FOR NONPARAMETRIC ESTIMATION OF STOCHASTIC DE-PENDENCE

Author(s) -

А. V. Lapko,

В. А. Лапко

Publication year - 2020

Publication title -

informatika i sistemy upravleniya

Language(s) - English

Resource type - Journals

eISSN - 1814-2419

pISSN - 1814-2400

DOI - 10.22250/isu.2020.66.95-103

Subject(s) - nonparametric statistics , computer science , dependency (uml) , mathematics , mathematical optimization , algorithm , statistical physics , econometrics , artificial intelligence , physics

A technique is proposed for constructing a nonparametric model of a multidimensional dependence in conditions of small volumes of initial statistical data. The method is based on a sequential procedure for building a nonparametric model in the space of argument lists of the restored dependency. The as-ymptotic properties of the developed model are investigated and the results of computational experi-ments are presented.

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