# How to use EventData correctly to model a trial sequence

I have trials of a component taken with successful trial denoted by 1 and 0 for failure. After every failure the improvements are incorporated before trials are run again. The trials are independent. But the improvements change the reliability distribution of the component. My question is Mathematica provides an EventData function, but what does it represent? I want to calculate what is the probability of success in the next trial.

data = {{2.8,1},{3.2,0},{4.3,1},{5.1,1},{6.3,0},{7.3,1},{8.9,1}};


Is the following correct?

dataset = EventData @@ Transpose @ data;
dist = EstimatedDistribution[dataset, someDistribution]

Probability[condition, x \[Distributed] dist]


How to define the condition that next trial is a success say at time 9.1 {9.1, ?} is a success?

• Have you seen SurvivalFunction[]? – J. M. is away Mar 19 '18 at 2:55
• Mathematica provides the survival distribution to fit the event data but the problem is on failure the distribution changes. Mathematica also has a reliability distribution and standby distribution function but this is the case where survival distribution changes with every failure do you know how to model this? – user13892 Mar 20 '18 at 10:51