May 1, 1970

On the limiting normality of posterior distributions

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Introduction . Suppose that we wish to make inferences about an unknown real parameter θ, and that we have a random sample of observations ( X l , X 2 , …, X n ) from a distribution which depends on θ.

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A. P. Dawid (Fri,) studied this question.

synapsesocial.com/papers/6a20a43eaa8e57945c6d98cd https://doi.org/https://doi.org/10.1017/s0305004100045953

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1On the Asymptotic Behaviour of Posterior Distributions1969 · 339 citations
2An Asymptotic Expansion for Posterior Distributions1967 · 66 citations
3On the Asymptotic Behavior of Bayes' Estimates in the Discrete Case1963 · 245 citations
4Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters1956 · 1,044 citations
5On the Asymptotic Behavior of Bayes Estimates in the Discrete Case II1965 · 333 citations

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