Time Trends for Binomial and Poisson Data

Dana Kelly () and Curtis Smith ()
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Dana Kelly: Idaho National Laboratory (INL)
Curtis Smith: Idaho National Laboratory (INL)

Chapter Chapter 5 in Bayesian Inference for Probabilistic Risk Assessment, 2011, pp 51-60 from Springer

Abstract: Abstract In this chapter, we will see how to develop models in which p and λ are explicit functions of time, relaxing the assumptions of constant p and constant λ in the binomial and Poisson distribution, respectively. This introduces new unknown parameters and makes the Bayesian inference significantly more complicated mathematically. However, modern tools such as OpenBUGS make this analysis no less tractable than the single-parameter cases analyzed earlier.

Date: 2011
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DOI: 10.1007/978-1-84996-187-5_5

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