Highest predictive density estimator in regression models

DOI10.1016/0304-4076(92)90088-9zbMath0761.62088OpenAlexW2039271149MaRDI QIDQ1194032

Shigeru Iwata

Publication date: 27 September 1992

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(92)90088-9

zbMATH Keywords

shrinkage estimatormarginal likelihoodposterior meanminimum riskempirical Bayes approachhighest predictive density estimatorHPRD estimatorHPRD priorslower bound on the Bayes factor

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Bayesian inference (62F15) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items

Bounding posterior means by model criticism ⋮ Lower bounds on bayes factors for a linear regression model

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Statistical decision theory and Bayesian analysis. 2nd ed
• Robust Bayes and empirical Bayes analysis with \(\epsilon\)-contaminated priors
• Stein estimation under elliptical distributions
• Smoothness Priors and Nonlinear Regression
• Testing a Point Null Hypothesis: The Irreconcilability of P Values and Evidence
• Sampling and Bayes' Inference in Scientific Modelling and Robustness
• Sets of Posterior Means with Bounded Variance Priors
• Parametric Empirical Bayes Inference: Theory and Applications
• The Weighted Likelihood Ratio, Linear Hypotheses on Normal Location Parameters
• On the Use of Incomplete Prior Information in Regression Analysis
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Linear Statistical Inference and its Applications