Sampling from Applied Probability Models

  • Eric A. Suess
  • Bruce E. Trumbo
Part of the Use R book series (USE R, volume 0)


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.


Exponential Distribution Unbiased Estimator Coverage Probability Parallel System Nonparametric Bootstrap 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Statistics and BiostatisticsCalifornia State University, East BayHaywardUSA

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