If one is using random numbers during simulation to generate pseudo-number generators it is important to check the 'quality' of these pseudo-random numbers. Donald E.Knuth [179] gives in chapt.3 a list of applicable tests in such a situation.
Generally it is assumed that the base numbers are assumed to be independent and uniformly distributed either as reals between zero and one or as integers between zero and some d-1.
- Theoretical: Chi-square test () applies to the situation when observations can fall into a finite number of categories
- Empirical: Equidistribution test (Knuth [179]:59f. In the wood1-scenario we have a move generator producing a random number out of the set
. In a first step one has to count the number of occurences for each possible pseudo random number
. Then one has to apply the chi-square test (see above).
- Empirical: Serial test
- Empirical: Partition test
- Empirical: Coupon Collector's test
- Empirical: Permutation test
- Empirical: Run test
- Empirical: Maximum-of-t test
- Empirical: Serial Correlation test
- Empirical: test on subsequences
Subsections
Gerd Doeben-Henisch
2012-03-31