On the recursive parameter estimation in the general discrete time statistical model
type: Item
instance of: scholarly article
title: On the recursive parameter estimation in the general discrete time statistical model
zbMATH Open document ID: 0933.62078
DOI: 10.1016/S0304-4149(97)00098-7
author: Teo Sharia
published in: Stochastic Processes and their Applications
publication date: 2000-03-01T00:00:00Z
review text: The author studies the limit behavior of recursive maximum likelihood estimators under some regularity and ergodicity assumptions on the logarithmic derivative of a transition density for a general statistical model. The consistency and asymptotic distribution are derived. The proved results are illustrated on several examples.
Mathematics Subject Classification ID: 62L20
Mathematics Subject Classification ID: 60G40
Mathematics Subject Classification ID: 62L12
zbMATH DE Number: 1409169
zbMATH Keywords: recursive estimation
zbMATH Keywords: conditional density of distributions
zbMATH Keywords: martingales
reviewed by: Marie Hušková
MaRDI profile type: Publication
cites work: Q3036531
cites work: Q3894827
cites work: Recursive estimators for stationary, strong mixing processes - a representation theorem and asymptotic distributions
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cites work: Statistical analysis of finite mixture distributions
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description: scientific article; zbMATH DE number 1409169