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Simulations Of Continuous Random Variables And Monte Carlo Methods

Author

Listed:
  • Sanda Micula

    (Babeş-Bolyai University, Cluj-Napoca, Romania)

  • Ioana D. Pop

    (University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca, Romania)

Abstract

In this paper we describe algorithms for computer simulations of some common continuous distributions and their implementation in MATLAB. We use Monte Carlo methods for estimating probabilities and other characteristics of random variables. The paper concludes with some interesting applications.

Suggested Citation

  • Sanda Micula & Ioana D. Pop, 2016. "Simulations Of Continuous Random Variables And Monte Carlo Methods," Romanian Economic Business Review, Romanian-American University, vol. 10(2), pages 435-447, December.
    • Handle: RePEc:rau:journl:v:10:y:2016:i:2:p:435-447
    as

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    File URL: http://www.rebe.rau.ro/RePEc/rau/jisomg/WI16/JISOM-WI16-A16.pdf
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    References listed on IDEAS

    as
    1. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
    2. Sanda Micula, 2015. "Statistical Computer Simulations And Monte Carlo Methods," Romanian Economic Business Review, Romanian-American University, vol. 9(2), pages 384-394, December.
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