Open AccessSEQUENTIAL PROCEDURE FOR NONPARAMETRIC ESTIMATION OF STOCHASTIC DE-PENDENCE
Author(s) -
А. В. Лапко,
В. А. Лапко
Publication year - 2020
Language(s) - English
DOI - 10.22250/isu.2020.66.95-103
Subject(s) - nonparametric statistics , computer science , dependency (uml) , estimation , nonparametric regression , argument (complex analysis) , mathematics , mathematical optimization , algorithm , statistical physics , econometrics , artificial intelligence , physics , biochemistry , chemistry , management , economics
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.