2018Applicationes MathematicaeRequires access

Application of copulas in the proof of the almost sure central limit theorem for the $k$th largest maxima of some random variables

Marcin Dudziński, Konrad Furmańczyk

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Abstract

Our aim is to prove the almost sure central limit theorem for the $k$th largest maxima $( M_{n}^{( k) }) $, $k=1,2,\ldots , $ of $X_{1},\ldots ,X_{n}$, $n \gt k$, where $( X_{i}) $ forms a stochastic process of identically distributed r.v.’s of continuous

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What this paper is about

Our aim is to prove the almost sure central limit theorem for the $k$th largest maxima $( M_{n}^{( k) }) $, $k=1,2,\ldots , $ of $X_{1},\ldots ,X_{n}$, $n \gt k$, where $( X_{i}) $ forms a stochastic process of identically distributed r.v.’s of continuous

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Available abstract

Our aim is to prove the almost sure central limit theorem for the $k$th largest maxima $( M_{n}^{( k) }) $, $k=1,2,\ldots , $ of $X_{1},\ldots ,X_{n}$, $n \gt k$, where $( X_{i}) $ forms a stochastic process of identically distributed r.v.’s of continuous

Key concepts: Maxima, Central limit theorem, Mathematics, Independent and identically distributed random variables, Limit (mathematics), Random variable, Combinatorics, Stochastic process

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