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Statistics Seminar - Vlad Stefan Barbu

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    • 06 Dec
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Vlad Stefan Barbu

Laboratory of Mathematics Raphaël Salem, University of Rouen – Normandy, France

Hypothesis testing based on weighted divergences

Abstract :
In this presentation, we first focus on a class of hypothesis tests for assessing the goodness-of-fit of a distribution, as well as on a class of homogeneity tests between two samples, in an iid framework. These tests are built on specific divergence measures, called weighted divergences, that allow us to focus more on a specific part of the distribution's support, while retaining also some information about the rest of the support. This methodology yields tests that are often more powerful than traditional tests, with comparable Type I error rates. We also present the associated asymptotic theory, along with corresponding Monte Carlo simulations, to examine the performance of the proposed tests. Additionally, we provide some elements for calculating test power. Extensions to Markovian and semi-Markovian cases will also be discussed.

  • Vendredi, 06 décembre 2024, 08h00
    Vendredi, 06 décembre 2024, 17h00
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