Interview with Nancy Reid

DOI10.1111/insr.12237OpenAlexW2762452793WikidataQ47037061 ScholiaQ47037061MaRDI QIDQ6064692

Ana-Maria Staicu

Publication date: 10 November 2023

Published in: International Statistical Review (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/insr.12237

zbMATH Keywords

composite likelihoodconditional inferencehigher order asymptoticsCOPSS award

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Aspects of likelihood inference
• On the robustness of maximum composite likelihood estimate
• On composite marginal likelihoods
• Influence functions for censored data
• On the asymptotic equivalence of two ranking methods for K-sample linear rank statistics
• Asymptotics and the theory of inference
• Saddlepoint methods and statistical inference. With comments and a rejoinder by the author
• The roles of conditioning in inference. With comments and rejoinder
• A note on pseudolikelihood constructed from marginal densities
• On probability matching priors
• Curvature and linear rank statistics
• The Role of Differential Geometry in Statistical Theory
• Local ancillarity
• Conditionality resolutions
• Likelihood as approximate pivotal distribution
• Approximations for densities of sufficient estimators
• The approximate distribution of partial serial correlation coefficients calculated from residuals from regression on Fourier series
• Estimating the median survival time
• Geometrical theory of asymptotic ancillarity and conditional inference
• A simple general formula for tail probabilities for frequentist and Bayesian inference
• Applications of bivariate and univariate local lyapunov exponents
• A note on the likelihood-ratio statistic under model misspecification
• Default Priors for Bayesian and Frequentist Inference
• Likelihood and higher‐order approximations to tail areas: A review and annotated bibliography
• Higher‐order asymptotics under model misspecification
• Accurate Directional Inference for Vector Parameters in Linear Exponential Families
• Past, Present, and Future of Statistical Science
• Mean loglikelihood and higher-order approximations
• Fiducial inference for location and scale parameters
• Accurate directional inference for vector parameters
• Applied Asymptotics

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