Statistical Science

Inference Functions and Quadratic Score Tests

Bruce G. Lindsay and Annie Qu

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Abstract

A general expository description is given of the use of quadratic score test statistics as inference functions. This methodology allows one to do efficient estimation and testing in a semiparametric model defined by a set of mean-zero estimating functions. The inference function is related to a quadratic minimum distance problem. The asymptotic chi-squared properties are shown to be the consequences of asymptotic projection properties. Shortcomings of the asymptotic theory are discussed and a bootstrap method is shown to correct for anticonservative testing behavior.

Article information

Source
Statist. Sci., Volume 18, Issue 3 (2003), 394-410.

Dates
First available in Project Euclid: 6 February 2004

Permanent link to this document
https://projecteuclid.org/euclid.ss/1076102427

Digital Object Identifier
doi:10.1214/ss/1076102427

Mathematical Reviews number (MathSciNet)
MR2061916

Zentralblatt MATH identifier
1055.62047

Keywords
Bootstrapping chi-squared test Edgeworth expansion generalized estimating equation generalized method of moments likelihood quadratic inference function quasi-likelihood semiparametric model

Citation

Lindsay, Bruce G.; Qu, Annie. Inference Functions and Quadratic Score Tests. Statist. Sci. 18 (2003), no. 3, 394--410. doi:10.1214/ss/1076102427. https://projecteuclid.org/euclid.ss/1076102427


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