Generalized Estimating Equations for Symmetric Distributions Observed with Admixture

A semiparametric two-component mixture model is considered, in which the distribution of one (primary) component is unknown and assumed symmetric. The distribution of the other component (admixture) is known. Generalized estimating equations are constructed for the estimation of the mixture proporti...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2011-01, Vol.40 (1), p.96-116
Main Authors: Maiboroda, Rostyslav, Sugakova, Olena
Format: Article
Language:English
Subjects:
Adaptive estimating equation
Admixtures
Asymptotic normality
Distribution theory
Econometrics
Economic models
Estimating
Exact sciences and technology
Finite mixture model
General topics
Mathematical analysis
Mathematics
Parametric inference
Primary 62G05, 62G20
Probability and statistics
Probability theory and stochastic processes
Sciences and techniques of general use
Secondary 62P10
Statistics
Studies
Symmetric distribution
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Summary:A semiparametric two-component mixture model is considered, in which the distribution of one (primary) component is unknown and assumed symmetric. The distribution of the other component (admixture) is known. Generalized estimating equations are constructed for the estimation of the mixture proportion and the location parameter of the primary component. Asymptotic normality of the estimates is demonstrated and the lower bound for the asymptotic covariance matrix is obtained. An adaptive estimation technique is proposed to obtain the estimates with nearly optimal asymptotic variances.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610920903350556