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Data-Driven k-Sample Tests

Summary: [This abstract is based on the author’s abstract.] A new approach to solving the non-parametric problem for independent continuous random variables introduces a net of semi-parametric models to solve testing problems for models within the net, and then combines the resulting statistics through model selection rules. This data-driven test also produces a class of k-sample tests that are flexible enough to allow construction of an omnibus, as well as other more complex solutions. A variant of the new solution used to detect high-frequency alterations is discussed.

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  • Topics: Statistics
  • Keywords: Ranking and selection, Data smoothing, Two-sample tests, Selection rule
  • Author: Wyłupek, Grzegorz
  • Journal: Technometrics