Confidence intervals (CI) are used to gauge the accuracy of bit error rate estimates produced by Monte Carlo (MC) simulations. This work attempts to objectively evaluate the performance of important sampling (IS) simulations by applying the same statistical analysis tool. While it is not possible to evaluate the minimum size CI for arbitrary IS estimates, it is possible to over-bound the interval using a technique called conservative confidence interval (CCI) estimation. This bounding procedure is applied to a simple IS biasing technique. While the IS estimate may be superior to the MC estimate, the CCI fails to support this claim
K. L. Kosbar and T. F. Chang, "Conservative Confidence Intervals of Importance Sampling Estimates," Proceedings of the IEEE Military Communications Conference, 1992. MILCOM '92, Institute of Electrical and Electronics Engineers (IEEE), Jan 1992.
The definitive version is available at http://dx.doi.org/10.1109/MILCOM.1992.244065
IEEE Military Communications Conference, 1992. MILCOM '92
Electrical and Computer Engineering
Keywords and Phrases
Monte Carlo Methods; Monte Carlo Simulations; Bit Error Rate Estimates; Conservative Confidence Interval Estimation; Error Statistics; Importance Sampling Estimates; Performance; Signal Processing; Statistical Analysis
Article - Conference proceedings
© 1992 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.