Approximately calibrated small sample inference about means from bivariate normal data with missing values

DOI10.1016/0167-9473(88)90090-4zbMath0726.62046OpenAlexW1974955843MaRDI QIDQ804141

Roderick J. A. Little

Publication date: 1988

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(88)90090-4

zbMATH Keywords

simulationincomplete dataJeffreys' priorhighest posterior density intervalsapproximate Bayesian posterior probability intervalscalibrated BayesCoverage propertiesFrequency propertiesmatching moments of the t distributionsmall bivariate sample

Mathematics Subject Classification ID

Point estimation (62F10) Bayesian inference (62F15)

Related Items

In Praise of Simplicity not Mathematistry! Ten Simple Powerful Ideas for the Statistical Scientist, Calibrated Bayes, for statistics in general, and missing data in particular, Discussion of ``Calibrated Bayes, for statistics in general, and missing data in particular by R. Little

Cites Work

• Bayesianly justifiable and relevant frequency calculations for the applied statistician
• Maximum Likelihood Estimates for a Multivariate Normal Distribution when some Observations are Missing
• The Calculation of Posterior Distributions by Data Augmentation
• Sampling and Bayes' Inference in Scientific Modelling and Robustness
• The Well-Calibrated Bayesian
• Inference and missing data
• Inference about means from incomplete multivariate data
• A test for equality of means of correlated variates with missing data on one response
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