The Use of Fuzzy A Priori Information for Estimation of Regression Parameters

Arnold S. Korkhin; Victor N. Mizernyi

doi:10.1615/JAutomatInfScien.v35.i1.50

Journal of Automation and Information Sciences

Editor-in-Chief: Arkadiy A. Chikriy (open in a new tab)

Associate Editors: Vyacheslav F. Gubarev (open in a new tab) Yuriy P. Kondratenko (open in a new tab) Nonna V. Turovyerova (open in a new tab)

Published 12 issues per year

ISSN Print: 1064-2315

ISSN Online: 2163-9337

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The Use of Fuzzy A Priori Information for Estimation of Regression Parameters

Volume 35, Issue 1, 2003, 12 pages

DOI: 10.1615/JAutomatInfScien.v35.i1.50

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Arnold S. Korkhin
National Mining University, Dnepropetrovsk

Victor N. Mizernyi
Vinnitsa National Technical University, Ukraine

ABSTRACT

A method of a priori information consideration, based on description of definition domain of regression parameters by equality constraints and by inequality constraints, where either right-hand or left-hand parts of constraints are prescribed fuzzy, is suggested. Statistical properties of estimates are studied. The described technique is applied for derivation of models of non-stationary stochastic systems, which can be reduced to a model of regression with switchings.

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