Bayes, Hilbert, and Least Squares,

Abstract

Stein (1950) and Rao (1965) show that much of the theory of least squares can be extended to abstract spaces. Lindley (1965, 1972) observes that the usual F test procedures can be derived from the Bayesian point of view by assuming vague prior knowledge of the parameters. These two ideas are discussed so as to be better known by statisticians interested in the general linear hypothesis.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1972
Accession Number
AD0758980

Entities

People

  • W. A. Thompson Jr.

Organizations

  • University of Missouri

Tags

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Space Objects