Review! We’re doing logistic and beta regression this time. These aren’t far apart, because the observable for both lives between 0 and 1; for logistic it is 0 or 1; for beta, […]
Mandatory! Read Part I. I will ignore all comments already answered in Part I. Download the code: mcmc.pred.R, mcmc.pred.examples.R. Update If you downloaded before, download again. This is version 0.2! You must […]
Previous post in the series (or click above on Class). Download the code: mcmc.pred.R, mcmc.pred.examples.R. If you downloaded before, download again. This is version 0.21! Only the example code changed since last […]
I saw colleague Deborah Mayo casting, or rather trying to cast, aspersions on Bayesian philosophy by saying there is “no prior”. Bayesians might not agree, but it’s true. Mayo’s right. There is […]
Introduction Here’s what we always want, but never get, using the old ways of doing statistics: The probability that some proposition Y is true given certain assumptions. Like this: (1) Pr(Y […]
Mandatory! Read Part I, Part II. I will ignore all comments already answered in Parts I & II. Download the code: mcmc.pred.R, mcmc.pred.examples.R. If you downloaded before, download again. This is version […]
Read Part I, Part II Ergodic in probability has a technical definition. Without going into mathematical details (which are fine except possibly when applied), a “sequence” is defined as a run of […]
Previous post in the series (or click above on Class). REVIEW! Download the code: mcmc.pred.R, mcmc.pred.examples.R. If you downloaded before, download again. This is version 0.3! Only the example code changed since […]
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