Management Science
A unified view of the IPA, SF, and LR gradient estimation techniques
Management Science
Bootstrap technology and applications
Technometrics
Fast simulation of the leaky bucket algorithm
WSC '94 Proceedings of the 26th conference on Winter simulation
Effective bandwidth and fast simulation of ATM intree networks
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
Bootstrap methods in computer simulation experiments
WSC '95 Proceedings of the 27th conference on Winter simulation
Importance sampling for large ATM-type queueing networks
WSC '96 Proceedings of the 28th conference on Winter simulation
An overview of derivative estimation
WSC '91 Proceedings of the 23rd conference on Winter simulation
Gradient estimation for ratios
WSC '91 Proceedings of the 23rd conference on Winter simulation
Simulating Stable Stochastic Systems, I: General Multiserver Queues
Journal of the ACM (JACM)
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Budget-Dependent Convergence Rate of Stochastic Approximation
SIAM Journal on Optimization
| Hi-index | 0.00 |
We are concerned with computing a confidence interval for the ratio E[Y]/E[X, where (X,Y) is a pair of random variables. This ratio estimation problem arises in, for instance, regenerative simulation. As an alternative to confidence intervals based on asymptotic normality, we study and compare different variants of the bootstrap for one-sided and two-sided intervals. We point out situations where these techniques provide confidence intervals with coverage much closer to the nominal value than do the classical methods.