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- Jose Blanchet, Peter Glynn
- 2008

Let (Xn : n ≥ 0) be a sequence of i.i.d. r.v.'s with negative mean. Set S0 = 0 and define Sn = X1 + · · · + Xn. We propose an importance sampling algorithm to estimate the tail of M = max{Sn : n ≥ 0} that is strongly efficient for both light and heavy-tailed increment distributions. Moreover, in the case of heavy-tailed increments and under additional… (More)

- Jose H. Blanchet, Jingchen Liu
- Proceedings of the 2006 Winter Simulation…
- 2006

Let (<i>X<inf>n</inf>: n</i> ≥ 0) be a sequence of iid rv's with mean zero and finite variance. We describe an efficient state-dependent importance sampling algorithm for estimating the tail of <i>S<inf>n</inf></i> = <i>X</i><inf>1</inf> + … + <i>X<inf>n</inf></i> in a large deviations framework as <i>n</i> ↗ ∞. Our algorithm can be… (More)

- Pierre L'Ecuyer, Jose H. Blanchet, Bruno Tuffin, Peter W. Glynn
- ACM Trans. Model. Comput. Simul.
- 2010

The asymptotic robustness of estimators as a function of a rarity parameter, in the context of rare-event simulation, is often qualified by properties such as bounded relative error (BRE) and logarithmic efficiency (LE), also called asymptotic optimality. However, these properties do not suffice to ensure that moments of order higher than one are well… (More)

- Jose H. Blanchet, Peter W. Glynn, Jingchen Liu
- Queueing Syst.
- 2007

We develop a strongly efficient rare-event simulation algorithm for computing the tail of the steady-state waiting time in a single server queue with regularly varying service times. Our algorithm is based on a state-dependent importance sampling strategy that is constructed so as to be straightforward to implement. The construction of the algorithm and its… (More)

Consider a sequence (X k : k ≥ 0) of regularly varying independent and identically distributed random variables with mean 0 and finite variance. We develop efficient rare-event simulation methodology associated with large deviation probabilities for the random walk (S n : n ≥ 0). Our techniques are illustrated by examples, including large deviations for the… (More)

- Søren Asmussen, Jose H. Blanchet, Sandeep Juneja, Leonardo Rojas-Nandayapa
- Annals OR
- 2011

We consider the problem of efficient estimation of tail probabilities of sums of correlated lognormals via simulation. This problem is motivated by the tail analysis of portfolios of assets driven by correlated Black-Scholes models. We propose two estimators that can be rigorously shown to be efficient as the tail probability of interest decreases to zero.… (More)

- Jose H. Blanchet, Peter W. Glynn
- 2015 Winter Simulation Conference (WSC)
- 2015

We present general principles for the design and analysis of unbiased Monte Carlo estimators for quantities such as α = g(E (X)), where E (X) denotes the expectation of a (possibly multidimensional) random variable X, and g(·) is a given deterministic function. Our estimators possess finite work-normalized variance under mild regularity… (More)

- Jose H. Blanchet
- Math. Oper. Res.
- 2013

- Jose H. Blanchet, Peter W. Glynn
- VALUETOOLS
- 2006

Let (<i>S<inf>n</inf> : n ≥ 0)</i> be a mean zero random walk (rw) with light-tailed increments. One of the most fundamental problems in rare-event simulation involves computing <i>P (S<inf>n</inf> > nβ)</i> for β > 0 when <i>n</i> is large. It is well known that the optimal exponential tilting (OET), although logarithmically… (More)

- Jose H. Blanchet, Jing Dong
- Proceedings Title: Proceedings of the 2012 Winter…
- 2012

Given a marked renewal point process (assuming that the marks are i.i.d.) we say that an unbounded region is stable if it contains finitely many points of the point process with probability one. In this paper we provide algorithms that allow to sample these finitely many points efficiently. We explain how exact simulation of the steady-state measure valued… (More)