2012
DOI: 10.1103/physreve.86.041115
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Weighted Kolmogorov-Smirnov test: Accounting for the tails

Abstract: Accurate goodness-of-fit tests for the extreme tails of empirical distributions is a very important issue, relevant in many contexts, including geophysics, insurance, and finance. We have derived exact asymptotic results for a generalization of the large-sample Kolmogorov-Smirnov test, well suited to testing these extreme tails. In passing, we have rederived and made more precise the approximate limit solutions found originally in unrelated fields, first in [L. Turban, J. Phys. A 25, 127 (1992)] and later in [… Show more

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Cited by 41 publications
(39 citation statements)
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“…In this domain the K-S test generates hugely overestimated confidence ranges, making us essentially blind to small but in principle detectable deviations. This problem was considered by Chicheportiche & Bouchaud (2012), who suggest a weighted modification of the K-S statistic (A1):…”
Section: Discussionmentioning
confidence: 99%
“…In this domain the K-S test generates hugely overestimated confidence ranges, making us essentially blind to small but in principle detectable deviations. This problem was considered by Chicheportiche & Bouchaud (2012), who suggest a weighted modification of the K-S statistic (A1):…”
Section: Discussionmentioning
confidence: 99%
“…This problem was revisited in detail in Ref. [71] in connection with a generalization of the KolmogorovSmirnov ("goodness-of-fit") test. In particular, the prefactor of the power law decay of Q(t) was computed.…”
Section: Brownian Walker In An Expanding Cagementioning
confidence: 99%
“…of neuronal data. A weighted Kolmogorov-Smirnov test with a refined goodness of fit estimate valid up to extreme tails [76].…”
Section: Discussionmentioning
confidence: 99%