Abstract
Let X be binomial (n, p), with n known. Suppose we wish to test H: (Equation presented) against K: (Equation presented). We consider the problem of choosing a prior distribution for p. Using a theory which introduces certain ideas of the Neyman-Pearson approach to Bayesian testing, it is shown that one need not specify a prior exactly, but only an equivalence class of priors. The equivalence class of the uniform prior over K allows us to specify certain situations involving only partial knowledge about the parameter in which one can use the uniform as the appropriate prior. © 1974, Taylor & Francis Group, LLC.
| Original language | English |
|---|---|
| Pages (from-to) | 740-743 |
| Number of pages | 4 |
| Journal | Journal of the American Statistical Association |
| Volume | 69 |
| Issue number | 347 |
| DOIs | |
| State | Published - 1974 |
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