Transformations of Random Variables

John H. Drew, Diane L. Evans, Andrew G. Glen and Lawrence M. Leemis
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John H. Drew: The College of William and Mary
Diane L. Evans: Rose-Hulman Institute of Technology
Andrew G. Glen: Colorado College
Lawrence M. Leemis: The College of William and Mary

Chapter 4 in Computational Probability, 2017, pp 47-56 from Springer

Abstract: Abstract This chapter presents a generalized version of the univariate change-of-variable technique for transforming continuous random variables. Extending a theorem from Casella and Berger [16] for many–to–1 transformations, we consider more general univariate transformations. Specifically, the transformation can range from 1–to–1 to many–to–1 on various subsets of the support of the random variable of interest. We also present an implementation of the theorem in APPL and present four examples.

Date: 2017
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DOI: 10.1007/978-3-319-43323-3_4

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