Studying the bandwidth in $$k$$ -sample smooth tests

Pablo Martínez-Camblor () and Jacobo Uña-Álvarez ()

Computational Statistics, 2013, vol. 28, issue 2, 875-892

Abstract: In this paper, the problem of bandwidth choice in smooth k-sample tests is considered. Three different bootstrap methods are discussed and implemented. All the methods persecute the bandwidth leading to the maximum power, while preserving the level of the test. The relative performance of the methods is investigated in a simulation study. Illustration through real medical data is provided. The main conclusion is that the bootstrap minimum method provides a good compromise between statistical power and conservativeness. Robustness of the methods with respect to the number of bootstrap resamples and practical limitations are discussed. Copyright Springer-Verlag 2013

Keywords: k-Sample tests; Kernel estimator; Bandwidth selection; Double bootstrap; Double minimum; BM algorithm (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:28:y:2013:i:2:p:875-892

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DOI: 10.1007/s00180-012-0333-1

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