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Zbl 1098.62053
Inglot, Tadeusz; Ledwina, Teresa
Asymptotic optimality of new adaptive test in regression model. (English)
[J] Ann. Inst. Henri Poincaré, Probab. Stat. 42, No. 5, 579-590 (2006). ISSN 0246-0203

Summary: This paper presents some results on asymptotic optimality of the test procedure introduced recently by {\it Y. Baraud, S. Huet} and {\it B. Laurent} [Adaptive tests of linear hypotheses by model selection. Ann. Stat. 31, 225--251 (2003; Zbl 1018.62037)]. The optimality relies on some comparisons of the ability of the new statistic to discriminate between the null hypothesis and convergent alternatives with capability of the respective Neyman--Pearson test.

MSC 2000:: *62G10 Nonparametric hypothesis testing
62G20 Nonparametric asymptotic efficiency
62G08 Nonparametric regression

Keywords: adaptive test; goodness-of-fit; model selection; tails; quantiles

Citations: Zbl 1018.62037

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