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The stochastic root-finding problem (SRFP) is that of solving a nonlinear system of equations using only a simulation that provides estimates of the functions at requested points. Equivalently, SRFPs seek locations where an unknown vector function attains a given target using only a simulation...
Analysts examining complex simulation models often conduct screening experiments to identify important factors. The controlled sequential bifurcation screening procedures CSB and CSB-X use a sequence of tests to classify factors as important or unimportant, while controlling Type I error and...
This article extends the use of classical autoregressive and moving average time-series models to the analysis of a variety of nonstationary discrete-event simulations. A thorough experimental evaluation shows that integrated and seasonal time-series models constitute very promising metamodels,...
A stochastic discrete-event simulation model of the natural history of Colorectal Cancer (CRC) is augmented with screening technology representations to create a base for simulating various screening strategies for CRC. The CRC screening strategies recommended by the American Gastroenterological...
We consider the problem of estimating the optimal parameter trajectory over a finite time interval in a parameterized stochastic differential equation (SDE), and propose a simulation-based algorithm for this purpose. Towards this end, we consider a discretization of the SDE over finite time...
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