Evaluating Kolmogorov's Distribution
Kolmogorov's goodness-of-fit measure, D_n , for a sample CDF has consistently been set aside for methods such as the D^+_n or D^-_n of Smirnov, primarily, it seems, because of the difficulty of computing the distribution of D_n . As far as we know, no easy way to compute that distribution has ever been provided in the 70+ years since Kolmogorov's fundamental paper. We provide one here, a C procedure that provides Pr(D_n < d) with 13-15 digit accuracy for n ranging from 2 to at least 16000. We assess the (rather slow) approach to limiting form, and because computing time can become excessive for probabilities>.999 with n's of several thousand, we provide a quick approximation that gives accuracy to the 7th digit for such cases.
Year of publication: |
2003-11-10
|
---|---|
Authors: | Marsaglia, George ; Tsang, Wai Wan ; Wang, Jingbo |
Published in: |
Journal of Statistical Software. - American Statistical Association. - Vol. 08.2003, i18
|
Publisher: |
American Statistical Association |
Saved in:
Saved in favorites
Similar items by person
-
Fast Generation of Discrete Random Variables
Marsaglia, George, (2004)
-
Some Difficult-to-pass Tests of Randomness
Marsaglia, George, (2002)
-
The Monty Python Method for Generating Gamma Variables
Marsaglia, George, (1999)
- More ...