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Design and Analysis of Monte Carlo Experiments

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Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

Abstract

By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (such as differential calculus), but are used for numerical experimentation. The goal of these experiments is to answer questions about the real world; i.e., the experimenters may use their models to answer what if questions this is also called sensitivity analysis.

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Authors and Affiliations

  1. Department of Information Management/Center for Economic Research (CentER), Tilburg University, Tilburg, The Netherlands

    Jack P. C. Kleijnen

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  1. Jack P. C. Kleijnen
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Correspondence to Jack P. C. Kleijnen .

Editor information

Editors and Affiliations

  1. Dept. Computational & Data, Sciences, George Mason University, University Drive 4400, Fairfax, 22030-4444, Virginia, USA

    James E. Gentle

  2. L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ., Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany

    Wolfgang Karl Härdle

  3. Dept. Socioinformation, Okayama University, Ridai-cho 1-1, Okayama, 700-0005, Japan

    Yuichi Mori

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Kleijnen, J.P.C. (2012). Design and Analysis of Monte Carlo Experiments. In: Gentle, J., Härdle, W., Mori, Y. (eds) Handbook of Computational Statistics. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21551-3_18

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