How does Radar Logic determine the parameters?
We use a fitting algorithm that tests a large number of possible values for each parameter until it finds the combination that best fits the data. Specifically, the algorithm fixes a set of shape parameters, starting with the parameters from the previous day as a first guess. For each day in the previous year, the algorithm then varies the position parameter and computes the log likelihood function (a standard statistical calculation that conveys how likely it is that a specific dataset could have been generated by a given distribution). It adds up the 365 individual log likelihood functions to get the cumulative log likelihood. It then tweaks the shape parameters and repeats the process. It continues to loop through these steps looking for better fits until it gets to a point that its tinkering stops making a discernable improvement, at which point it locks down the optimized parameters for the day.
Related Questions
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