Minimal area regions are constructed for Brownian paths and perturbed Brownian paths. While the theoretical optimal region cannot be obtained in closed form, we provide practical confidence regions based on numerical approximations and local time arguments. These regions are used to provide informal convergence assessments for both Monte Carlo and Markov Chain Monte Carlo experiments, via the Brownian asymptotic approximation of cumulative sums
AbstractWe assume a drift condition towards a small set and bound the mean square error of estimator...
AbstractCarefully injected noise can speed the average convergence of Markov chain Monte Carlo (MCMC...
Prices of path dependent options may be modeled as expectations of functions of an infinite sequence...
When considering a Monte Carlo estimation procedure, the path produced by successive partial estimat...
La version de travail s'intitule "Brownian Confidence Bands on Monte Carlo Output"Minimal area regio...
AbstractThis paper deals with the estimate of errors introduced by finite sampling in Monte Carlo ev...
This paper deals with the estimate of errors introduced by finite sampling in Monte Carlo evaluation...
We construct proxy regions based on local time arguments and consider numerical approximations. Thes...
Markov Chain Monte Carlo (MCMC) methods are widely used and preferred when the sampling distribution...
We are concerned with the probability that a standard Brownian motion W(t) crosses a curved boundary...
We present an iterative sampling method which delivers upper and lower bounding processes for the Br...
Let b(t), 0t[mu]. The problem of setting a fixed width confidence interval for [theta]=1[+45 degree ...
We provide a mathematical study of the modified Diffusion Monte Carlo (DMC) algorithm introduced in ...
It is well known that Monte Carlo method can be used to estimate the area of a region which cannot b...
We consider the bias arising from time discretization when estimating the threshold crossing probabi...
AbstractWe assume a drift condition towards a small set and bound the mean square error of estimator...
AbstractCarefully injected noise can speed the average convergence of Markov chain Monte Carlo (MCMC...
Prices of path dependent options may be modeled as expectations of functions of an infinite sequence...
When considering a Monte Carlo estimation procedure, the path produced by successive partial estimat...
La version de travail s'intitule "Brownian Confidence Bands on Monte Carlo Output"Minimal area regio...
AbstractThis paper deals with the estimate of errors introduced by finite sampling in Monte Carlo ev...
This paper deals with the estimate of errors introduced by finite sampling in Monte Carlo evaluation...
We construct proxy regions based on local time arguments and consider numerical approximations. Thes...
Markov Chain Monte Carlo (MCMC) methods are widely used and preferred when the sampling distribution...
We are concerned with the probability that a standard Brownian motion W(t) crosses a curved boundary...
We present an iterative sampling method which delivers upper and lower bounding processes for the Br...
Let b(t), 0t[mu]. The problem of setting a fixed width confidence interval for [theta]=1[+45 degree ...
We provide a mathematical study of the modified Diffusion Monte Carlo (DMC) algorithm introduced in ...
It is well known that Monte Carlo method can be used to estimate the area of a region which cannot b...
We consider the bias arising from time discretization when estimating the threshold crossing probabi...
AbstractWe assume a drift condition towards a small set and bound the mean square error of estimator...
AbstractCarefully injected noise can speed the average convergence of Markov chain Monte Carlo (MCMC...
Prices of path dependent options may be modeled as expectations of functions of an infinite sequence...