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2011•Shuxue de shijian yu renshiRequires access

Sufficient Conditions of Weak Consistency of MQLE in Quasi-Likelihood Nonlinear Models

Xia Tian

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Abstract

Quasi-likelihood nonlinear models(QLNM) include generalized linear models as a special case.This paper proposes some sufficient conditions of weak consistency of maximum quasi- likelihood estimator(MQLE) in QLNM,in which the condition of the moment is weaker than that of strong consistency of MQLE in the existing literature.

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What this paper is about

Quasi-likelihood nonlinear models(QLNM) include generalized linear models as a special case.This paper proposes some sufficient conditions of weak consistency of maximum quasi- likelihood estimator(MQLE) in QLNM,in which the condition of the moment is weaker than that of strong consistency of MQLE in the existing literature.

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Available abstract

Quasi-likelihood nonlinear models(QLNM) include generalized linear models as a special case.This paper proposes some sufficient conditions of weak consistency of maximum quasi- likelihood estimator(MQLE) in QLNM,in which the condition of the moment is weaker than that of strong consistency of MQLE in the existing literature.

Key concepts: Consistency (knowledge bases), Strong consistency, Weak consistency, Quasi-maximum likelihood, Mathematics, Moment (physics), Nonlinear system, Estimator

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