Ancillaries and conditional inference (with comments and rejoinder)

DOI10.1214/088342304000000323zbMath1100.62534OpenAlexW1981436989MaRDI QIDQ2503934

Donald A. S. Fraser

Publication date: 22 September 2006

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/088342304000000323

zbMATH Keywords

likelihoodconditional inferencepivotalsensitivity directionsAncillariesinference directions

Mathematics Subject Classification ID

Foundations and philosophical topics in statistics (62A01) Sufficient statistics and fields (62B05)

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Cites Work

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• The roles of conditioning in inference. With comments and rejoinder
• Strong matching of frequentist and Bayesian parametric inference
• An ancillarity paradox which appears in multiple linear regression
• Some Problems Connected with Statistical Inference
• Ancillarity Principle and a Statistical Paradox
• Saddle point approximation for the distribution of the sum of independent random variables
• Some remarks on conditional and unconditional inference for location-scale models
• Some Ancillary Statistics and Their Properties
• A simple general formula for tail probabilities for frequentist and Bayesian inference
• Simple and accurate inference for the mean of the gamma model
• Likelihood for component parameters
• Regression Analysis, Nonlinear or Nonnormal: Simple and Accurate p Values From Likelihood Analysis
• Two new properties of mathematical likelihood
• The Logic of Inductive Inference
• Bayes, Likelihood, or Structural
• On Confidence Limits and Sufficiency, with Particular Reference to Parameters of Location