2013
DOI: 10.1007/s10559-013-9483-6
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Using a priori information in regression analysis

Abstract: The paper considers the methods to evaluate regression parameters under indefinite a priori information of two types: fuzzy and stochastic. Fuzzy a priori information is assumed to be formulated on the basis of fuzzy notions of the model designer. Stochastic a priori information is systems of equations, which are linear in regression parameters and whose right-hand sides are random variables. Regression parameters may both be constant and vary in time. A classification of the evaluation methods using indefinit… Show more

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Cited by 2 publications
(1 citation statement)
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“…In (Korkhin, 2013), the methods of estimation of regression parameters under fuzzy and stochastic indefinite and a priori information are considered. Regression parameters might be both constant and varying in time.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In (Korkhin, 2013), the methods of estimation of regression parameters under fuzzy and stochastic indefinite and a priori information are considered. Regression parameters might be both constant and varying in time.…”
Section: Literature Reviewmentioning
confidence: 99%