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December 2003 Asymptotics and the theory of inference
N. Reid
Ann. Statist. 31(6): 1695-2095 (December 2003). DOI: 10.1214/aos/1074290325

Abstract

Asymptotic analysis has always been very useful for deriving distributions in statistics in cases where the exact distribution is unavailable. More importantly, asymptotic analysis can also provide insight into the inference process itself, suggesting what information is available and how this information may be extracted. The development of likelihood inference over the past twenty-some years provides an illustration of the interplay between techniques of approximation and statistical theory.

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N. Reid. "Asymptotics and the theory of inference." Ann. Statist. 31 (6) 1695 - 2095, December 2003. https://doi.org/10.1214/aos/1074290325

Information

Published: December 2003
First available in Project Euclid: 16 January 2004

zbMATH: 1042.62022
MathSciNet: MR2036388
Digital Object Identifier: 10.1214/aos/1074290325

Subjects:
Primary: 62-02
Secondary: 62E20 , 62F05

Keywords: $p$* , $P$-values , $r$* , ancillarity , approximation , Bayesian inference , Conditioning , Laplace approximation , likelihood , matching priors , saddlepoint approximation , tail area , tangent exponential model

Rights: Copyright © 2003 Institute of Mathematical Statistics

Vol.31 • No. 6 • December 2003
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