Changes between Version 10 and Version 11 of UWSummerStatsWorkshop

Timestamp:

Jul 22, 2015, 12:46:33 PM (9 years ago)

Author:

iovercast

Comment:

--

UWSummerStatsWorkshop

@@ -95 +95 @@
   * "Pseudo-Gibbs sampler"
  * Stronger modelling assumptions tend to underestimate uncertainty.
+* Wednesday AM
+ * Bayesian Model Choice
+  * Posterior odds = Prior odds x Bayes Factor
+   * Posterior odds: ratio of posterior probabilities of model given data
+   * Prior odds: ratio of probability of the models
+   * Bayes factor: likelihood of model 1 over model 2 (data given the model)
+  * Bayes factor ("marginal likelihood"), isolate the model from the data, and see how prior assumptions on the model will change the results.
+  * Bayes factor does not rely on prior odds, which is why people use it. Interpreted in light of prior odds. Interpretation depends on context, and on prior odds.
+  * If you collect enough data the posterior odds will converge toward infinity with probability 1 in favor of the true model.
+ * Sensitivity analysis: Bayes factors can be peculiarly sensitive to the priors in ways you can't expect, so testing different priors could be informative.
+ * Model choice: Don't use flat priors on things that are only present in one model
+
 ==== quotes ====
 * "Out of all the tomorrows we might experience...."
 * "Uncertainty is, intrinsically, personal."
 * "Random draws to mapped calls..."
+* "It's very hard to get rational behavior out of a committee."
+* "The problem is: How flat matters."
+* "How to specify your prior: look into your heart and think about what you know."
+* "You're going to be wrong whatever you do. These are cartoons of reality, none of these models are right."