Click the Event Plot disclosure icon to see a plot of the failure or censoring times. The following Event Plot for the Censor Labels.jmp sample data table shows a mix of censored data (Event Plot for MixedCensored Data).
In the data table, rightcensored values have one time value and a censor value or two time values.
Censored Data Types shows the data table for mixedcensored data.
When you select a distribution method, the following events occur:
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The cumulative distribution estimates appear on the probability plot (in Comparing Distributions, the magenta and yellow lines).

Comparing Distributions shows an example of the Compare Distributions report.
To change the statistic used to sort the report, select Comparison Criterion from the Life Distribution red triangle menu. If the three criteria agree on the best fit, the sorting does not change. See Life Distribution Platform Options for details about this option.
See Nonparametric Fit for more information about nonparametric estimates.
Specifies the value of parameters. Enter the new location or scale, select the appropriate check box, and then click Update. JMP reestimates the other parameters, covariances, and profilers based on the new parameters.
Note that for the Weibull distribution, the Fix Parameter option lets you select the Weibayes method.
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Location and Scale Priors  Specify parameters for prior distributions. Select the red triangle next to the prior distributions to select a different distribution for each parameter. You can enter new values for the hyperparameters of the priors. You can also enter the number of Monte Carlo simulation points and a random seed (should be a positive integer greater than 1), and select to show a scatter plot.

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Quantile and Parameter Priors  Specify ranges for quantile and scale. Select the red triangle next to the prior distributions to select a different distribution for each parameter. You can enter new values for the probability and limits. You can also enter the number of Monte Carlo simulation points and a random seed (should be a positive integer greater than 1), and select to show a scatter plot (Meeker and Escobar 1998).

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Failure Probability Priors  Specify failure probability by estimates, error percentages, and ranges. You can enter new values for the failure probability, probability estimates, and estimate errors. A prior probability function versus time plot is displayed. You can also enter the number of Monte Carlo simulation points and a random seed (should be a positive integer greater than 1), and select to show a scatter plot (Kaminskiy and Krivtsov, 2005).

After you click Fit Model, a new report called Bayesian Estimates shows summary statistics of the posterior distribution of each parameter and a scatterplot of the simulated posterior observations. In addition, profilers help you visualize the fitted life distribution based on the posterior medians.
If you have zero failure data, it is possible to run a Bayesian estimation. A preference, Weibayes Only for Zero Failure Data, exists that ensures the Weibayes method is used for zero failure data analysis. The preference is on by default (similar to the behavior in previous releases). If you have zero failure data and want to run a full Bayesian estimation, you can uncheck the platform preference to run a full analysis. To access the preference, select File > Preferences > Platform > Life Distribution.
Predicts failure probabilities, survival probabilities, and quantiles for specific time and probability values. Each estimate has its own section. Enter a new time and press the Enter key to see the new estimate. To calculate multiple estimates, click the plus sign, enter another time in the box, and then press Enter.
For more information about the distributions used in parametric estimates, see Parametric Distributions.
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To see estimates for another distribution, select the distribution in the Scale column. Change the Scale illustrates how changing the scale affects the distribution fit.

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To exclude a specific failure cause from the analysis, select Omit next to the cause. The graph is instantly updated.

Omit Competing Causes illustrates the effect of omitting causes.
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To change the distribution for a specific failure cause, select the distribution from the Distribution list. Click Update Model to show the new distribution fit on the graph, and the Cause Summary report is updated.

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The Parm_n columns show the parametric estimates for each cause.

To show the profiler for each individual cause distribution, select Show Subdistributions from the Competing Cause red triangle menu. The Individual Subdistribution Profiler for Cause report appears under the other profilers. Select a cause from the list to see a profiler of the distribution’s CDF.