Random Variables and Probability Distributions

Dirk P. Kroese and Joshua Chan
Additional contact information
Dirk P. Kroese: The University of Queensland, School of Mathematics and Physics

Chapter Chapter 2 in Statistical Modeling and Computation, 2014, pp 23-61 from Springer

Abstract: Abstract Specifying a model for a random experiment via a complete description of the sample space Ω and probability measure $$\mathbb{P}$$ may not always be necessary or convenient. In practice we are only interested in certain numerical measurements pertaining to the experiment. Such random measurements can be included into the model via the notion of a random variable.

Keywords: Inverse-transform Method; Acceptance Rejection Method; Continuous Random Variables; Common Discrete Distributions; Uniform Random Number Generator (search for similar items in EconPapers)
Date: 2014
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:sprchp:978-1-4614-8775-3_2

Ordering information: This item can be ordered from
http://www.springer.com/9781461487753

DOI: 10.1007/978-1-4614-8775-3_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().