2014Communication in Statistics- Theory and MethodsRequires access

Large Deviation Principles for Sequences of Maxima and Minima

Rita Giuliano, Claudio Macci

Open publisher page 16 citations

Abstract

In this article, we consider sequences of i.i.d. random variables and, under suitable conditions on the (common) distribution function, we prove large deviation principles for sequences of maxima, minima and pairs formed by maxima and minima. The i.i.d. random variables can be either unbounded or bounded; in the first case maxima and minima have to be suitably normalized.

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What this paper is about

In this article, we consider sequences of i.i.d. random variables and, under suitable conditions on the (common) distribution function, we prove large deviation principles for sequences of maxima, minima and pairs formed by maxima and minima. The i.i.d. random variables can be either unbounded or bounded; in the first case maxima and minima have to be suitably normalized.

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Available abstract

In this article, we consider sequences of i.i.d. random variables and, under suitable conditions on the (common) distribution function, we prove large deviation principles for sequences of maxima, minima and pairs formed by maxima and minima. The i.i.d. random variables can be either unbounded or bounded; in the first case maxima and minima have to be suitably normalized.

Key concepts: Maxima and minima, Maxima, Bounded function, Mathematics, Statistical physics, Function (biology), Mathematical analysis, Physics

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