Very weak expansions for sequentially designed experiments: Linear models

DOI10.1214/aos/1176347257zbMath0683.62039OpenAlexW2059384385MaRDI QIDQ1824969

Michael B. Woodroofe

Publication date: 1989

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

Full work available at URL: https://doi.org/10.1214/aos/1176347257

zbMATH Keywords

maximum likelihood estimatorlinear modelslikelihood functionfunctional formprior distributionsStein's identityAsymptotic expansions for sampling distributionsconficence curveconfidence functionalmartingale convergene theorem

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Sequential statistical design (62L05)

Related Items (21)

Stagewise learning for noisy \(k\)-ary preferences ⋮ Some simple corrected confidence intervals following a sequential test ⋮ CORRECTED CONFIDENCE SETS FOR SEQUENTIALLY DESIGNED EXPERIMENTS: EXAMPLES1* ⋮ A Study of Expansions of Posterior Distributions ⋮ An O'Brien-Fleming sequential trial for comparing three treatments ⋮ Corrected Confidence Levels for Adaptive Nonlinear Regression ⋮ Sequential confidence intervals with fixed-proportional accuracy for the mean of NEF-PVF distributions ⋮ Approximate confidence intervals after a sequential clinical trial comparing two exponential survival curves with censoring ⋮ Construction of a Confidence Interval By Triple Sampling ⋮ Corrected confidence intervals based on the signed root transformation for multi-parameter sequentially designed experiments ⋮ Expansions for multivariate densities ⋮ Asymptotic normality of posterior distributions for generalized linear mixed models ⋮ On the validity of the formal Edgeworth expansion for posterior densities ⋮ Asymptotic posterior normality for multiparameter problems ⋮ Real-time Bayesian parameter estimation for item response models ⋮ Approximate bias calculations for sequentially designed experiments ⋮ Corrected confidence intervals for adaptive nonlinear regression models ⋮ Approximate confidence sets for a stationary \(AR(p)\) process ⋮ Sharp connections between Berry-Esseen characteristics and Edgeworth expansions for stationary processes ⋮ Corrected confidence intervals for parameters in adaptive linear models ⋮ Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation

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