Given sample data and reference distributions, the function tests the hypothesis that the sample data comes from the distributions (Hypothesis-Test Mode). Given the test results, the function finds the distribution that best matches the sample data (Best-Match Mode).
The Distribution Matching function is composed of the functions DistributionMatchReduce and DistributionMatchMultiInput. DistributionMatchReduce supports these distributions:
- For continuous variables:
- Beta
- Cauchy
- ChiSq
- Exponential
- F
- Gamma
- Lognormal
- Normal
- T
- Triangular
- Uniform
- Weibull
- For discrete variables:
- Binomial
- Geometric
- Negative binomial
- Poisson
- Uniform
For evaluating the fit of the distribution to the data, the function supports these tests:
- Anderson-Darling test
- Kolmogorov-Smirnov test
- Cramér-von Mises criterion (hypothesis testing only)
- Pearson’s Chi-squared test