Bivariate Transformations of Random Variables

John H. Drew, Diane L. Evans, Andrew G. Glen and Lawrence M. Leemis
Additional contact information
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 5 in Computational Probability, 2017, pp 57-72 from Springer

Abstract: 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).

Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-43323-3_5

Ordering information: This item can be ordered from
http://www.springer.com/9783319433233

DOI: 10.1007/978-3-319-43323-3_5

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().