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Conference Papers Year : 2019

ABOUT THE DISCRETIZED MAXIMUM LIKELIHOOD ESTIMATOR

Abstract

The most well-known and used statistical estimation procedure is probably the Maximum Likelihood. Unfortunately, apart from rather elementary situations, the analysis of its performance requires complex probablistic tools, namely Empirical Process Theory. Examples can be found, for instance, in the books by Ibragimov and Has'minskii [5], van der Vaart [9], van de Geer [3] or Massart [8]. Our purpose here is to describe a discretized version of the method, which is not so well-known, but with the advantage that one can derive its non-asymptotic performance from elementary tools. We shall explain the method, give its performance and provide several illustrative examples.
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Dates and versions

hal-03913351 , version 1 (17-01-2023)

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  • HAL Id : hal-03913351 , version 1

Cite

Lucien Birgé. ABOUT THE DISCRETIZED MAXIMUM LIKELIHOOD ESTIMATOR. Congrès de la Société Mathématique de France - SMF 2018, Société Mathématique de France, Jun 2018, Lille, France. pp.355-373. ⟨hal-03913351⟩
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