ISSN:
1572-9052
Keywords:
Asymptotic distribution
;
generalized estimating equation
;
covariance structure analysis
;
pseudo maximum likelihood
;
generalized least squares
;
equivariant M-estimation
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract In a variety of statistical problems the estimate Θn of a parameter Θ is defined as the root of a generalized estimating equation Gn(Θnγn)=0 where γn is an estimate of a nuisance parameter γ. We give sufficient conditions for the asymptotic normality of #x0398;n defined in this way and derive their asymptotic distribution. A circumstance under which the asymptotic distribution of #x0398;n will not be influenced by that of γn) is noted. As an example, we consider a covariance structure analysis in which both the population mean and the population fourth-order moment are nuisance parameters. Applications to pseudo maximum likelihood, generalized least squares with estimated weights, and M-estimation with an estimated scale parameter are discussed briefly.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1004122007440
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