Technical Note—Generation of Variates from Distribution Tails | Zendy

Bruce W. Schmeiser | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Technical Note—Generation of Variates from Distribution Tails

Author(s) -

Bruce W. Schmeiser

Publication year - 1980

Publication title -

operations research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.797

H-Index - 140

eISSN - 1526-5463

pISSN - 0030-364X

DOI - 10.1287/opre.28.4.1012

Subject(s) - weibull distribution , exponential function , gamma distribution , convolution random number generator , function (biology) , mathematics , heavy tailed distribution , computer science , beta distribution , distribution (mathematics) , algorithm , mathematical optimization , exponential distribution , probability distribution , random variate , statistics , random variable , mathematical analysis , evolutionary biology , biology

The well known acceptance/rejection algorithm for generating random values on a computer is specialized for distribution tails. Using an exponential majorizing function and a linear minorizing function, the tail algorithm becomes particularly efficient. Specific algorithms are given for the normal, gamma, Weibull and beta distributions. While the algorithms can be used alone, it is anticipated that their major value will be to serve as components of algorithms for complete distributions.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research