Most of my recent life distribution analyses have involved distributions with DS and/or ZI components. JMP supports only a few DS distributions and a few ZI distributions, and the support is inconsistent across platforms (Life Distribution, Survival, Distribution). I have not seen a single distribution in JMP that simultaneously includes DS and ZI components, although my data does. As a result I have been forced to do the analysis outside of JMP. This seriously erodes my value proposition for JMP.
DS and ZI are effectively degenerate modes which are mixed into other distributions. The Life Distribution platform already supports mixtures generally. Rather than adding a combinatorially large set of new DS, ZI, and DSZI distributions, I propose adding DS and ZI as modes available as mixtures.
With a relatively low development effort, this will allow us to model DS Exponential, DSZI normal, ZI Fréchet, etc., as well as decoupling the degenerate modes from other modes in a mixture. For example, DS + Normal + Weibull as opposed to drawing a distinction between DS Normal + Weibull vs. DS Weibull + Normal, or DS + Weibull + Weibull as opposed to DS Weibull + Weibull.
We would further benefit as users by having statistics for these mixed distributions readily available. When I do these analyses outside JMP, I lose easy access to prediction intervals, i.e. intervals on reliability at time t, or intervals for B5 life. Incorporating the degenerate modes into the Life Distribution mixture tool would be an easy way to access all of this functionality.
Ideally, other platforms could be similarly enhanced, both for distribution analysis or for expected value analysis (Monte Carlo, sensitivity, etc.).
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