Under certain conditions on the integrand, quasi-Monte Carlo methods for estimating integrals (expectations) converge faster asymptotically than Monte Carlo methods. Motivated by ...
Shane G. Henderson, Belinda A. Chiera, Roger M. Co...
We propose a framework for optimization problems based on particle filtering (also called Sequential Monte Carlo method). This framework unifies and provides new insight into rand...
This paper compares Monte Carlo methods, lattice rules, and other low-discrepancy point sets on the problem of evaluating asian options. The combination of these methods with vari...
We present a new localization algorithm called Sensor Resetting Localization which is an extension of Monte Carlo Localization. The algorithm adds sensor based resampling to Monte...
We develop a financial model for a manufacturing process where quality can be affected by an assignable cause. We evaluate the options associated with applying a statistical proce...