On the strong consistency of least squares estimates in stochastic regression models with associated errors

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Strong consistency of the least-squares estimates in stochastic regression models is established considering associated errors with finite variance and assuming a moderate asymptotic condition on the stochastic regressors. Strong consistency of the ridge estimates is also obtained for some biasing parameters in the referred
set of assumptions.
Original languageEnglish
Title of host publicationMathematical Methods in Science and Mechanics
EditorsNikos Mastorakis, Francesco Mainardi, Mariofanna Milanova
Place of PublicationLisbon
PublisherWorld Scientific and Engineering Academy and Society
Pages58-64
Number of pages7
ISBN (Print)978-960-474-396-4
Publication statusPublished - 1 Nov 2014

Publication series

NameMathematics and Computers in Science and Engineering Series
PublisherWSEAS Press
Number33
ISSN (Print)2227-4588

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