Author： Xia Tian
Publisher： Taylor & Francis Ltd
ISSN： 0361-0926
Source： Communications in Statistics: Theory and Methods, Vol.37, Iss.15, 2008-09, pp. : 2358-2368
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Abstract
Quasi-likelihood nonlinear models (QLNM) are a further extension of generalized linear models by only specifying the expectation and variance functions of the response variable. In this article, some mild regularity conditions are proposed. These regularity conditions, respectively, assure the existence, strong consistency, and the asymptotic normality of the maximum quasi-likelihood estimator (MQLE) in QLNM.
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