Bayes Estimates for the Linear Model

Bayes Estimates for the Linear Model

The usual linear statistical model is reanalyzed using Bayesian methods and the concept of exchangeability. The general method is illustrated by applications to two-factor experimental designs and multiple regression.

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Bibliographische Detailangaben
Veröffentlicht in:Journal of the Royal Statistical Society. Series B, Methodological Methodological, 1972-09, Vol.34 (1), p.1-41
Hauptverfasser: Lindley, D. V., Smith, A. F. M.
Format: Artikel
Sprache:eng
Schlagworte:
admissibility
bayes estimates
Bayes estimators
Estimation methods
Estimators
exchangeability
least squares
linear model
Linear models
Mathematical functions
matrix inversion
Maximum likelihood estimation
Multiple regression
Prior learning
ridge regression
Statistical discrepancies
Statistical variance
two‐factor experimental design
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Beschreibung
Zusammenfassung:The usual linear statistical model is reanalyzed using Bayesian methods and the concept of exchangeability. The general method is illustrated by applications to two-factor experimental designs and multiple regression.
ISSN:0035-9246
1369-7412
2517-6161
1467-9868
DOI:10.1111/j.2517-6161.1972.tb00885.x