DocumentCode
1352427
Title
Random Variate Generation for Monte Carlo Experiments
Author
Leemis, Lawrence ; Schmeiser, Bruce
Author_Institution
The University of Oklahoma, School of Industrial Engineering; 202 West Boyd, Suite 124; Norman, Oklahoma USA.
Issue
1
fYear
1985
fDate
4/1/1985 12:00:00 AM
Firstpage
81
Lastpage
85
Abstract
We discuss methods for generating observations from specified distributions, based on a taxonomy that emphasizes analogies between methods based on the probability-density and cumulative-distribution functions and methods based on the hazard rate and cumulative hazard functions. Four categories are identified: inversion methods, linear combination methods, majorizing methods and special properties. Examples are given of each.
Keywords
Computational modeling; Computer simulation; Distributed computing; Distribution functions; Hazards; Monte Carlo methods; Probability; Random number generation; Random variables; Taxonomy; Competing risks; Hazard function; Random numbers; Simulation; Thinning;
fLanguage
English
Journal_Title
Reliability, IEEE Transactions on
Publisher
ieee
ISSN
0018-9529
Type
jour
DOI
10.1109/TR.1985.5221941
Filename
5221941
Link To Document