The Bayes Plot report gives another approach to determining which effects are active. This report helps you compute posterior probabilities using a Bayesian approach. This method, due to Box and Meyer (1986), assumes that the estimates are a mixture from two distributions. The majority of the estimates, corresponding to inactive effects, are assumed to be pure random normal noise with variance σ2. The remaining estimates, the active ones, are assumed to come from a contaminating distribution that has a variance K times larger than σ2.
The specifications window, showing default settings for a Bayes Plot for the Bicycle.jmp sample data table, is shown in Figure 2.46. Clicking Go in this window updates the report to show Posterior probabilities for each of the terms and a bar chart (Figure 2.47).
1.
Select Help > Sample Data Library and open Bicycle.jmp.
2.
Select Analyze > Fit Model.
3.
Select Y and click Y.
4.
Select HBars through Brkfast and click Add.
5.
Click Run.
Figure 2.46 Bayes Plot Specifications
7.
Click Go to calculate the posterior probabilities.
Figure 2.47 Bayes Plot Report

Help created on 10/11/2018