Abstract
Neyman [7] was the first to propose a change in measure in the context of goodness of fit problems. This provided an alternative density to the one for the null hypothesis. Hoeffding introduced a change of measure formula for the ranks of the observed data which led to obtaining locally most powerful rank tests. In this paper, we review these methods and propose a new approach which leads on the one hand to new derivations of existing statistics. On the other hand, we exploit these methods to obtain Bayesian applications for ranking data.
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Work supported by the Natural Sciences and Engineering Council of Canada, Grant OGP0009068.
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Alvo, M. (2020). Change of Measure Applications in Nonparametric Statistics. In: La Rocca, M., Liseo, B., Salmaso, L. (eds) Nonparametric Statistics. ISNPS 2018. Springer Proceedings in Mathematics & Statistics, vol 339. Springer, Cham. https://doi.org/10.1007/978-3-030-57306-5_2
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DOI: https://doi.org/10.1007/978-3-030-57306-5_2
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