Over the decades that have passed since they were introduced, copulae still remain a very
powerful tool for modeling and estimating multivariate distributions. This work gives an …

Estimating the unknown density from which a given independent sample originates is more
difficult than estimating the mean in the sense that, for the best popular nonparametric …

The Creation Process is an algorithm that transforms a static network model into a dynamic
one. It is the basis of different variance reduction methods designed to make efficient …

The Marshall-Olkin (MO) copula model has emerged as the standard tool for capturing
dependence between components in failure analysis in reliability. In this model, shocks …

The creation and the destruction processes (CPs and DPs) are the basis of many efficient
Monte Carlo methods for estimating the unreliability of highly reliable networks on both, the …

In this article, we show a limit result for the reliability function of a system—that is, the
probability that the whole system is still operational after a certain given time—when the …

Stochastic Simulation and Monte Carlo Methods Page 1 Draft date: February 2, 2024
Stochastic Simulation and Monte Carlo Methods Pierre L’Ecuyer Département d’Informatique …

We consider a network whose links have random capacities and in which a certain target
amount of flow must be carried from some source nodes to some destination nodes. Each …

We present a neural network framework for the simulation of independent random variables
from arbitrary distributions. The framework includes two neural networks that are trained …

A stochastic binary system (SBS) is a multicomponent on‐off system subject to random
independent failures on its components. After potential failures, the state of the subsystem is …