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  • Converting the results of a constructed Bayesian inference calculation into a distribution; or
  • Constructing a spliced or mixed distribution by averaging, or manipulating probability density functions for the component distributions; or
  • knowing the pdf or pmf of a specific distribution not available with Crystal Ball.in your software


Application

We can use the same techniques as explained in Method 3 to create distributions from a set of points:

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If the data set is of the form of {x, f(x)}, we can use the a General distribution in Crystal Ball with the use of Crystal Ball's Custom Distribution;or 

If the data set is of the form {x, F(x)}, we can use the Cumulative distribution in Crystal Ball with the use of Crystal Ball's Custom Distribution; or 

If the data set is of the form {x, p(x)}, we can use the Discrete distribution in Crystal Ball with the use of Crystal Ball's Custom Distribution.


The {x} values must be in ascending order for the General and Cumulative distribution because they construct a distribution shape. For the Discrete distribution this is unnecessary because it is simply a list of values.

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