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View Code? Open in Web Editor NEWNotes for Gelman's Bayesian Data Analysis 3
Notes for Gelman's Bayesian Data Analysis 3
Hey, I'm so confused. Is there a quick transformation of variables example?!?!
All three are used in the chapter and have clear connections with each other. In fact, I went through these over mathcation, so if I can find my notes it would be really fast to write up...
In the same sense that many of the common distributions can be related to each other, many of the conjugates for distributions follow simple patterns. For example, see John Cook's page.
What information about conjugates is most critical to retain? General patterns? Common conjugates? In many cases they're easy to derive, but the arithmetic is tedious..
See also here for good summary of many conjugate priors.
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