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Bivariate Transformations of Random Variables

In: Computational Probability

Author

Listed:
  • 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)

Abstract

This chapter extends the work in the previous chapter in order to automate the bivariate change-of-variables technique for bivariate continuous random variables with arbitrary distributions. The algorithm from the previous chapter for univariate change-of-variables was originally devised by Glen et al. [37]. The bivariate transformation procedure presented in this chapter handles 1-to-1, k-to-1, and piecewise k-to-1 transformations for both independent and dependent random variables. We also present other procedures that operate on bivariate random variables (e.g., calculating correlation and marginal distributions).

Suggested Citation

  • John H. Drew & Diane L. Evans & Andrew G. Glen & Lawrence M. Leemis, 2017. "Bivariate Transformations of Random Variables," International Series in Operations Research & Management Science, in: Computational Probability, edition 2, chapter 5, pages 57-72, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-43323-3_5
    DOI: 10.1007/978-3-319-43323-3_5
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