Adaptive Testing on a Regression Function at a Point
Timothy Armstrong
No 1957, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University
Abstract:
We consider the problem of inference on a regression function at a point when the entire function satisfies a sign or shape restriction under the null. We propose a test that achieves the optimal minimax rate adaptively over a range of Holder classes, up to a log log n term, which we show to be necessary for adaptation. We apply the results to adaptive one-sided tests for the regression discontinuity parameter under a monotonicity restriction, the value of a monotone regression function at the boundary, and the proportion of true null hypotheses in a multiple testing problem.
Keywords: Adaptive inference; Regression discontinuity; Identification at infinity (search for similar items in EconPapers)
JEL-codes: C12 C14 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2014-08, Revised 2014-10
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (2)
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Working Paper: Adaptive Testing on a Regression Function at a Point (2015)
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