A conditional Berry-Esseen bound and a conditional large deviation result without Laplace transform. Application to hashing with linear probing
classification
🧮 math.PR
keywords
deviationlargeresultberry-esseenboundconditionaldistributedhashing
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\noindent We study the asymptotic behavior of a sum of independent and identically distributed random variables conditioned by a sum of independent and identically distributed integer-valued random variables. We prove a Berry-Esseen bound in a general setting and a large deviation result when the Laplace transform of the underlying distribution is not defined in a neighborhood of zero. Then we present several combinatorial applications. In particular, we prove a large deviation result for the model of hashing with linear probing.
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