Consistency and asymptotic normality of maximum likelihood estimation for Gaussian Markov processes from discrete observations
type: Item
instance of: scholarly article
title: Consistency and asymptotic normality of maximum likelihood estimation for Gaussian Markov processes from discrete observations
zbMATH Open document ID: 0855.62068
DOI: 10.1007/BF02613898
author: Birgit Gaschler
published in: Metrika
publication date: 1996-06-11T00:00:00Z
full work available at URL: https://eudml.org/doc/176634
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 62F12
zbMATH DE Number: 887156
zbMATH Keywords: weak consistency
zbMATH Keywords: asymptotic normality
zbMATH Keywords: maximum likelihood estimation
zbMATH Keywords: discrete observations
zbMATH Keywords: independent Gaussian Markov processes
zbMATH Keywords: Ornstein Uhlenbeck process
zbMATH Keywords: asymptotic simultaneous confidence regions
MaRDI profile type: Publication
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OpenAlex ID: W1963490123
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description: scientific article; zbMATH DE number 887156