Rick Picard

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In modeling particle transport through a medium, the path of a particle behaves as a transient Markov Chain. We are interested in characteristics of the particle's movement conditional on its starting state which take the form of a \score" accumulated with each transition. Importance sampling is an essential variance reduction technique in this setting, and(More)
BACKGROUND Concern over bio-terrorism has led to recognition that traditional public health surveillance for specific conditions is unlikely to provide timely indication of some disease outbreaks, either naturally occurring or induced by a bioweapon. In non-traditional surveillance, the use of health care resources are monitored in "near real" time for the(More)
Adaptive importance sampling involves successively estimating the function of interest and then constructing an importance sampling scheme built on the estimate. Here, we investigate such a scheme used in simulations of Markov chains derived from particle transport problems. Previous work had shown that for nite state spaces the convergence was exponential,(More)
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