Plug-in estimation of d-dimensional density minimum volume set of a rare event in a complex system

J Morio and R Pastel

Journal of Risk and Reliability, 2012, vol. 226, issue 3, 337-345

Abstract: Various reliability or hedging problems boil down to quantile estimation. However, real-life systems are usually multidimensional and thus often imply multidimensional density minimum volume set estimation which is usually done with Monte Carlo simulations. Increasing safety standards create a need for density minimum volume set estimation with low probability that crude Monte Carlo cannot fulfil. This paper proposes a new importance sampling algorithm that estimates efficiently multidimensional density minimum volume sets for extreme probability. It also presents some numerical results on a simple bidimensional Gaussian case and on a realistic launcher impact safety zone estimation.

Keywords: density volume set; rare event simulation; importance sampling; complex system engineering; Monte Carlo methods (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:226:y:2012:i:3:p:337-345

DOI: 10.1177/1748006X11426973

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