Abstract
A one-parameter model is a class of sampling distributions that is indexed by a single unknown parameter. In this chapter we discuss Bayesian inference for two one-parameter models: the binomial model and the Poisson model. In addition to being useful statistical tools, these models also provide a simple environment within which we can learn the basics of Bayesian data analysis, including conjugate prior distributions, predictive distributions and confidence regions.
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© 2009 Springer Science+Business Media, LLC
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Hoff, P.D. (2009). One-parameter models. In: A First Course in Bayesian Statistical Methods. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-92407-6_3
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DOI: https://doi.org/10.1007/978-0-387-92407-6_3
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Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-92299-7
Online ISBN: 978-0-387-92407-6
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