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Monte Carlo and Quasi-Monte Carlo Methods 2010 pp 373–384Cite as

QMC Computation of Confidence Intervals for a Sleep Performance Model

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 23))

Abstract

A five-dimensional Bayesian forecasting model for cognitive performance impairment during sleep deprivation is used to approximately determine confidence intervals for psychomotor vigilance task (PVT) prediction. Simulation is required to locate the boundary of a confidence region for the model pdf surface. Further simulation is then used to determine PVT lapse confidence intervals as a function of sleep deprivation time. Quasi-Monte Carlo simulation methods are constructed for the two types of simulations. The results from these simulations are compared with results from previous methods, which have used various combinations of grid-search, numerical optimization and simple Monte Carlo methods.

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Authors and Affiliations

  1. Mathematics Department, Washington State University, Pullman, WA, 99164-3113, USA

    Alan Genz & Amber Smith

Authors
  1. Alan Genz
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  2. Amber Smith
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Correspondence to Alan Genz .

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Editors and Affiliations

  1. , Institute of Applied Mathematics, University of Warsaw, Banacha 2, Warsaw, 02-097, Poland

    Leszek Plaskota

  2. , Institute of Applied Mathematics, University of Warsaw, Banacha 2, Warsaw, 02-097, Poland

    Henryk Woźniakowski

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Genz, A., Smith, A. (2012). QMC Computation of Confidence Intervals for a Sleep Performance Model. In: Plaskota, L., Woźniakowski, H. (eds) Monte Carlo and Quasi-Monte Carlo Methods 2010. Springer Proceedings in Mathematics & Statistics, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27440-4_19

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