Deriving the Posterior Distribution

Marcel van Oijen ()

Chapter Chapter 5 in Bayesian Compendium, 2020, pp 29-32 from Springer

Abstract: Abstract In the preceding chapters, we discussed how we can assign a prior distribution for our parameters, and how to choose a likelihood function that captures the information content of our data. So all that is left, is to apply Bayes’ Theorem (Eq. ( 1.2 )) to derive our desired posterior distribution. Note that when talking about the posterior, we use the phrase ‘deriving the’ distribution rather than ‘assigning a’ distribution.

Date: 2020
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DOI: 10.1007/978-3-030-55897-0_5

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