This paper aims at comparing theoretical approximations of the tail of the maximum of stochastic processes and the corresponding numerical evaluations. More particularly, we focus on the Pickands or double sum method, the Rice method, the Euler Characteristic method and a new one called the Poisson method. The numerical evaluation, performed using mainly Quasi Monte-Carlo integration and adaptations of the programs of Genz, show the domains of validity of each method
summary:If a stochastic process can be approximated with a Wiener process with positive drift, then ...
This book presents a wide range of well-known and less common methods used for estimating the accura...
This thesis consists of four papers A, B, C and D. Paper A and B treats the simulation of stochastic...
This paper aims at comparing theoretical approximations of the tail of the maximum of stochastic pro...
This article proposes computing sensitivities of upper tail probabilities of random sums by the sadd...
We study an approach for the evaluation of approximation and solution methodsfor multistage linear s...
This paper deals with the problem of obtaining methods to compute the distribution of the maximum of...
his paper will trace the history and development of a useful stochastic method for approximating cer...
This paper examines the properties of various approximation methods for solving stochastic dynamic p...
based on Markov chain simulation have been in use for many years. The validity of these algorithms d...
This paper investigates the accuracy of a perturbation method in approximating the solution to stoch...
In this dissertation, we propose two new types of stochastic approximation (SA) methods and study th...
Numerical Methods for Simulation of Stochastic Differential Equations Stochastic differential equati...
This paper discusses the use of the Robbins Monro algorithm and the Kiefer Wolfowitz algorithm in th...
We compare and evaluate the performance of four widely used numerical solution methods to dynamic ra...
summary:If a stochastic process can be approximated with a Wiener process with positive drift, then ...
This book presents a wide range of well-known and less common methods used for estimating the accura...
This thesis consists of four papers A, B, C and D. Paper A and B treats the simulation of stochastic...
This paper aims at comparing theoretical approximations of the tail of the maximum of stochastic pro...
This article proposes computing sensitivities of upper tail probabilities of random sums by the sadd...
We study an approach for the evaluation of approximation and solution methodsfor multistage linear s...
This paper deals with the problem of obtaining methods to compute the distribution of the maximum of...
his paper will trace the history and development of a useful stochastic method for approximating cer...
This paper examines the properties of various approximation methods for solving stochastic dynamic p...
based on Markov chain simulation have been in use for many years. The validity of these algorithms d...
This paper investigates the accuracy of a perturbation method in approximating the solution to stoch...
In this dissertation, we propose two new types of stochastic approximation (SA) methods and study th...
Numerical Methods for Simulation of Stochastic Differential Equations Stochastic differential equati...
This paper discusses the use of the Robbins Monro algorithm and the Kiefer Wolfowitz algorithm in th...
We compare and evaluate the performance of four widely used numerical solution methods to dynamic ra...
summary:If a stochastic process can be approximated with a Wiener process with positive drift, then ...
This book presents a wide range of well-known and less common methods used for estimating the accura...
This thesis consists of four papers A, B, C and D. Paper A and B treats the simulation of stochastic...