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An Empirical Bayes Approach to Statistics

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Breakthroughs in Statistics

Part of the book series: Springer Series in Statistics ((PSS))

Abstract

Let X be a random variable which for simplicity we shall assume to have discrete values x and which has a probability distribution depending in a known way on an unknown real parameter A,

$$ p\left( {x|\lambda } \right) = Pr[X = x|\Lambda = \lambda ], $$
((1))

A itself being a random variable with a priori distribution function

$$ G\left( \lambda \right) = \operatorname{P} r[\Lambda {\text{ }}\underline \leqslant {\text{ }}\lambda ]. $$
((2))

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References

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© 1992 Springer Science+Business Media New York

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Robbins, H.E. (1992). An Empirical Bayes Approach to Statistics. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-0919-5_26

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  • DOI: https://doi.org/10.1007/978-1-4612-0919-5_26

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94037-3

  • Online ISBN: 978-1-4612-0919-5

  • eBook Packages: Springer Book Archive

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