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- W2609999188 abstract "This chapter describes the construction of Bayesian intervals for data generated from the normal distribution, binomial distribution, and Poisson distribution. It extends these methods to consider the construction of Bayesian intervals for the more complicated situation involving hierarchical models. The chapter discusses the construction of Bayesian intervals for the binomial distribution, Bayesian intervals for the Poisson distribution, and Bayesian intervals for the normal distribution. In each section, it shows how to compute credible intervals for the distribution parameter(s), functions of the parameter(s), and Bayesian tolerance and prediction intervals. Because of the preceding equivalence (or near-equivalence) of results obtained by using non-Bayesian intervals and Bayesian intervals constructed using diffuse prior distributions, the chapter focuses mainly on comparing Bayesian credible intervals constructed using diffuse versus informative prior distributions. Bayesian statistical intervals based on a Jeffreys prior distribution generally have coverage probabilities that are close to the nominal credible level." @default.
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- W2609999188 date "2017-03-27" @default.
- W2609999188 modified "2023-09-25" @default.
- W2609999188 title "Bayesian Statistical Intervals for the Binomial, Poisson, and Normal Distributions" @default.
- W2609999188 doi "https://doi.org/10.1002/9781118594841.ch16" @default.
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