EconPapers    
Economics at your fingertips  
 

Generating Continuous Random Variates

Nick T. Thomopoulos
Additional contact information
Nick T. Thomopoulos: Illinois Institute of Technology, Stuart School of Business

Chapter Chapter 4 in Essentials of Monte Carlo Simulation, 2013, pp 27-44 from Springer

Abstract: Abstract This chapter shows how to transform the continuous uniform random variates, u∼U(0,1), to random variates for a variable that comes from one of the common continuous probability distributions. The probability distributions described here are the following: the continuous uniform, exponential, Erlang, gamma, beta, Weibull, normal, lognormal, chi-square, student’s t, and Fishers F. The chapter also shows how to use the (Hasting’s) approximation formulas for the standard normal distribution.

Keywords: Cumulative Distribution Function; Standard Normal Distribution; Approximation Formula; Gamma Variate; Continuous Uniform (search for similar items in EconPapers)
Date: 2013
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:978-1-4614-6022-0_4

Ordering information: This item can be ordered from
http://www.springer.com/9781461460220

DOI: 10.1007/978-1-4614-6022-0_4

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 ().

 
Page updated 2026-06-25
Handle: RePEc:spr:sprchp:978-1-4614-6022-0_4