Abstract
In this chapter, and Chapter 18, we shall deal with situations where both the null hypothesis and the class of alternatives may be nonparametric and so, as a result, it may be difficult even to construct tests (or confidence regions) that satisfactorily control the level (exactly or asymptotically). For such situations, we shall develop methods which achieve this modest goal under fairly general assumptions. A secondary aim will then be to obtain some idea of the power of the resulting tests.
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Lehmann, E.L., Romano, J.P. (2022). Permutation and Randomization Tests. In: Testing Statistical Hypotheses. Springer Texts in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-70578-7_17
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DOI: https://doi.org/10.1007/978-3-030-70578-7_17
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