Minimum Kolmogorov–Smirnov test statistic parameter estimates

Abstract

We present and implement an algorithm for computing the parameter estimates in a univariate probability model for a continuous random variable that minimizes the Kolmogorov–Smirnov test statistic. The algorithm uses an evolutionary optimization technique to solve for the estimates. Several simulation experiments demonstrate the effectiveness of this approach.

Keywords:

• Algorithm
• Evolutionary algorithm
• Continuous probability distributions
• Goodness-of-fit tests
• Input modeling

Acknowledgement

The authors gratefully acknowledge the support of NASA Langley Research Center- NAG-1-2077.