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[ascl:2006.007] TATTER: Two-sAmple TesT EstimatoR

TATTER (Two-sAmple TesT EstimatoR) performs two-sample hypothesis test. The two-sample hypothesis test is concerned with whether distributions p(x) and q(x) are different on the basis of finite samples drawn from each of them. This ubiquitous problem appears in a legion of applications, ranging from data mining to data analysis and inference. This implementation can perform the Kolmogorov-Smirnov test (for one-dimensional data only), Kullback-Leibler divergence, and Maximum Mean Discrepancy (MMD) test. The module performs a bootstrap algorithm to estimate the null distribution and compute p-value.

Code site:
https://github.com/afarahi/tatter
Described in:
https://ui.adsabs.harvard.edu/abs/2021A%26C....3400445F
Bibcode:
2020ascl.soft06007F

Views: 3208

ascl:2006.007
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