On the first-order efficiency and asymptotic normality of the maximum likelihood estimator obtained from dependent observations

R Heijmans and Jan Magnus ()

No 293077, University of Amsterdam, Actuarial Science and Econometrics Archive from University of Amsterdam, Faculty of Economics and Business

Abstract: In this paper we study the first-order efficiency and asymptotic normality of the maximum likelihood estimator obtained from dependent observations. Our conditions are somewhat weaker than usual, in that we do not require convergences in probability to be uniform or third-order derivatives to exist; moreover, the conditions will appear to be ready verifiable. This paper builds on Witting and None's result concerning the asymptotic normality of the maximum likelihood estimator obtained from dependent and identically distributed observations, and on a martingale theorem by McLeish.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 43
Date: 1984-10
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Related works:
Journal Article: ON THE FIRST–ORDER EFFICIENCY AND ASYMPTOTIC NORMALITY OF MAXIMUM LIKELIHOOD ESTIMATORS OBTAINED FROM DEPENDENT OBSERVATIONS (1986)
Working Paper: ON THE FIRST-ORDER EFFICIENCY AN DASYMPTOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS (1985)
Working Paper: ON THE FIRST-ORDER EFFICIENCY AND ASYMPOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS (1983)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:amstas:293077

DOI: 10.22004/ag.econ.293077

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