Saddlepoint approximations and tests based on multivariate \(M\)-estimates.

DOI10.1214/aos/1059655909zbMath1056.62023OpenAlexW2077075438MaRDI QIDQ1434010

Elvezio Ronchetti, G. Alastair Young, John Robinson

Publication date: 1 July 2004

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aos/1059655909

zbMATH Keywords

bootstrap testscomposite hypothesesnonparametric likelihoodsmooth functions of \(M\)-estimators

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Parametric hypothesis testing (62F03) Nonparametric estimation (62G05) Approximations to statistical distributions (nonasymptotic) (62E17) Asymptotic properties of parametric tests (62F05)

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Uses Software

• bootlib

Cites Work

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• On the density of minimum contrast estimators
• Small sample asymptotic expansions for multivariate M-estimates
• Large deviation and other results for minimum contrast estimators
• Saddlepoint approximations for marginal and conditional probabilities of transformed variables
• The density of multivariate \(M\)-estimates.
• Dual likelihood
• General Saddlepoint Approximations of Marginal Densities and Tail Probabilities
• On the relationship between empirical likelihood and empirical saddlepoint approximation for multivariate M-estimators
• Nonparametric Confidence Limits by Resampling Methods and Least Favorable Families
• Small-Sample Confidence Intervals
• Empirical likelihood ratio confidence intervals for a single functional
• Robust Bounded-Influence Tests in General Parametric Models
• Multivariate Saddlepoint test for the wrapped normal model
• Approximations for marginal densities of M‐estimators