Abstract
In Chapter 3, we used the sampling method to find probabilities and expectations involving a random variable with a distribution that is easy to describe but with a density function that is not explicitly known. In this chapter, we explore additional applications of the sampling method. The examples are chosen because of their practical importance or theoretical interest. Some- times, analytic methods can be used to get exact results for special cases, thus providing some confidence in the validity of more general simulation results. Also, in an elementary way, some of the examples and problems show how simulation can be useful in research. At least they have illustrated this to us personally because we have gained insights from simulation in these settings that we might never have gained by analytic means.
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© 2010 Springer Science+Business Media, LLC
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Suess, E.A., Trumbo, B.E. (2010). Sampling from Applied Probability Models. In: Introduction to Probability Simulation and Gibbs Sampling with R. Use R, vol 0. Springer, New York, NY. https://doi.org/10.1007/978-0-387-68765-0_4
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DOI: https://doi.org/10.1007/978-0-387-68765-0_4
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Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-40273-4
Online ISBN: 978-0-387-68765-0
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