Efficient importance sampling for large sums of independent and identically distributed random variables

We discuss estimating the probability that the sum of nonnegative independent and identically distributed random variables falls below a given threshold, i.e., P ( ∑ i = 1 N X i ≤ γ ) , via importance sampling (IS). We are particularly interested in the rare event regime when N is large and/or γ is...

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Veröffentlicht in:	Statistics and computing Jg. 31; H. 6; S. 1 - 21
Hauptverfasser:	Ben Rached, Nadhir, Haji-Ali, Abdul-Lateef, Rubino, Gerardo, Tempone, Raúl
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.11.2021 Springer Nature B.V Springer Verlag (Germany)
Schlagworte:	Artificial Intelligence Computer Science Importance sampling Mathematics and Statistics Modeling and Simulation Parameters Polynomials Probability and Statistics in Computer Science Probability density functions Random variables Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Twisting 62P30 Exponential twisting 65C05 Gamma IS PDF Rare event Importance sampling exponential twisting rare event Gamma IS PDF AMS subject classifications: 65C05
ISSN:	0960-3174, 1573-1375
Online-Zugang:	Volltext
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