Tip: Select the Comparison Criterion option to change the criterion for finding the best distribution.
where is one of the supported distributions, k is the number of components in the mixture, and the wi are positive weights that sum to 1. The Fit Mixture option attempts to identify clusters of observations that are drawn from each of the component distributions, Fi(x). It estimates the parameters of the mixture and the probability that an observation is drawn from any given component.
Click Go to fit the desired mixture. The Model List is updated with the model that you fit, and a report with the name of the mixture model is added.
The Comparison Criterion red triangle option does not affect the order of models in the Model List.
Parameter estimates are given for each distribution in the mixture. The Parameter column also includes parameters called Portion <i>, where i = 1, 2, .., k-1. These are estimates of the weights wi for the mixture. Since the weights sum to 1, the kth weight can be computed from the first k - 1 weights.
1.
Select Help > Sample Data Library and open Reliability/Mixture Demo.jmp.
2.
Select Analyze > Reliability and Survival > Life Distribution.
3.
Select Y1 and click Y, Time to Event.
4.
5.
Select Fit Mixture from the red triangle menu next to Life Distribution.
6.
Type 2 in the Quantity box next to Weibull.
7.
Select Separable Clusters in the Starting Value Methods panel.
8.
Fit Mixture for Weibull (2)
9.
Type 1 next to Lognormal and 1 next to Weibull.
10.
Fit Mixture for Lognormal(1), Weibull(1)
2.
Select Analyze > Distribution.
4.
Check Histograms Only.
5.
6.
In the histogram for Lognormal(1), Weibull(1) - Predicted Probability from Weibull, click in the bar corresponding to the value near 1.
Histograms for Mixture Probabilities
where represents the cumulative failure distributions for the ith risk and k is the number of components (or risks) in the mixture. The Fit Competing Risk Mixture option attempts to identify clusters of observations that are drawn from each of the component distributions, Fi(x). It estimates the parameters of the mixture and the probability that an observation is drawn from any given component.
The Competing Risk Mixture report is structured in a fashion that mirrors the Mixture report. See Mixture. However, the Fit Competing Risk Mixture reports do not show a Density Overlay plot. They show a Distribution Overlay plot instead.