Parametric Techniques on Other Distributions- THE KOLMOGOROV-SMIRNOV (K-S) TEST
Parametric Techniques on Other Distributions THE KOLMOGOROV-SMIRNOV (K-S) TEST The chi-square test is no doubt the most popular of all methods of comparing two distributions. Since many market-oriented applications other than the ones . However, the best test for our pur poses may well be the K-S test. This very efficient test is applicable to unbinned distributions that are a function of a single independent vari able. All cumulative density functions have a minimum value of 0 and a maximum value of 1. What goes on in between differentiates them. The K-S test measures a very simple variable, D, which is defined as the maximum absolute value of the difference between two distributions' cumulative density functions. To perform the K-S test is relatively simple. N objects are standardized and sorted in ascending order. As we go through these sorted and standardized trades, the cumulative probability is how ever many trades we've gone through divided b