**Definition**

The PPCC plot is formed by:

- Vertical axis: Probability plot correlation coefficient;
- Horizontal axis: Value of shape parameter.

That is, for a series of values of the shape parameter, the correlation coefficient is computed for the probability plot associated with a given value of the shape parameter. These correlation coefficients are plotted against their corresponding shape parameters. The maximum correlation coefficient corresponds to the optimal value of the shape parameter. For better precision, two iterations of the PPCC plot can be generated; the first is for finding the right neighborhood and the second is for fine tuning the estimate.

The PPCC plot is used first to find a good value of the shape parameter. The probability plot is then generated to find estimates of the location and scale parameters and in addition to provide a graphical assessment of the adequacy of the distributional fit.

The PPCC plot answers the following questions:

- What is the best-fit member within a distributional family?
- Does the best-fit member provide a good fit (in terms of generating a probability plot with a high correlation coefficient)?
- Does this distributional family provide a good fit compared to other distributions?
- How sensitive is the choice of the shape parameter?

Read more about this topic: Probability Plot Correlation Coefficient Plot

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