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- Jose H. Blanchet
- 2007

Importance sampling has been reported to produce algorithms with excellent empirical performance in counting problems. However, the theoretical support for its efficiency in these applications has been very limited. In this paper, we propose a methodology that can be used to design efficient importance sampling algorithms for counting and test their… (More)

Consider a sequence (Xk : 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 (Sn : 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, Henry Lam
- Math. Oper. Res.
- 2014

We develop rare-event simulation methodology for the analysis of loss events in a manyserver loss system under quality-driven regime, focusing on the steady-state loss probability (i.e. fraction of lost customers over arrivals) and the behavior of the whole system leading to loss events. The analysis of these events requires working with the full… (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, Alexandre Stauffer
- Random Struct. Algorithms
- 2013

A binary contingency table is an m×n array of binary entries with row sums r = (r1, . . . , rm) and column sums c = (c1, . . . , cn). The configuration model generates a contingency table by considering ri tokens of type 1 for each row i and cj tokens of type 2 for each column j, and then taking a uniformly random pairing between type-1 and type-2 tokens.… (More)

This paper develops the first class of algorithms that enable unbiased estimation of steady-state expectations for multidimensional reflected Brownian motion. In order to explain our ideas, we first consider the case of compound Poisson (possibly Markov modulated) input. In this case, we analyze the complexity of our procedure as the dimension of the… (More)

- Jose H. Blanchet, Sandeep Juneja, Leonardo Rojas-Nandayapa
- 2008 Winter Simulation Conference
- 2008

Our focus is on efficient estimation of tail probabilities of sums of correlated lognormals. This problem is motivated by the tail analysis of portfolios of assets driven by correlated Black-Scholes models. We propose three different procedures that can be rigorously shown to be asymptotically optimal as the tail probability of interest decreases to zero.… (More)

The contribution of this paper is to introduce change of measure based techniques for the rare-event analysis of heavy-tailed stochastic processes. Our changes-of-measure are parameterized by a family of distributions admitting a mixture form. We exploit our methodology to achieve two types of results. First, we construct Monte Carlo estimators that are… (More)

- 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)