Parametric Distribution Fitting
Parametric Distribution Fitting |
Description | Parametric distribution fitting is the process used to select a statistical distribution that best fits a data set. |
Why to use | Statistical Analysis |
When to use | To decide the distribution best suited for data description. | When not to use | When the distribution of data is known. |
Prerequisites |
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Input | A dataset containing continuous data. | Output | Best fit distributions sorted by the Goodness of Fit tests. |
Statistical Methods used | — | Limitations | It can be used only on continuous data. It doesn’t work on categorical/textual data. |
In Distribution fitting, first, the data is matched against probability distributions using parametric distribution-fitting. For each distribution, this fitting establishes a set of parameters that best describe the data characteristics. Next, one of the several Goodness-of-Fit tests is employed to determine the closeness of each fit. Finally, out of the results obtained, the highest-ranked fit is selected to represent the data.
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