New algorithms for generating Poisson variates
type: Item
instance of: scholarly article
title: New algorithms for generating Poisson variates
zbMATH Open document ID: 0702.65004
DOI: 10.1016/0377-0427(90)90344-Y
published in: Journal of Computational and Applied Mathematics
publication date: 1990-01-01T00:00:00Z
review text: The author discusses three algorithms for generating Poisson (\(\lambda\)) random variates. The first one is the KPFRAC algorithm, designed for \(\lambda <0\), the second one is KPLOW, for \(0<\lambda \leq 30\) and the third one is KEMPOIS, for 10\(\leq \lambda \leq 5000\). The conclusions of the work is that these algorithms prove that new features can be incorporated into the search approach and make it more competitive. A mixed routine which uses KPLOW, when \(\lambda <30\) and KEMPOIS, when \(\lambda\geq 30\) is indicated and so the speed of calculus is higher.
reviewed by: A.Donescu
Mathematics Subject Classification ID: 65C10
zbMATH DE Number: 4151692
zbMATH Keywords: varying-parameter algorithms
zbMATH Keywords: sequential searches
zbMATH Keywords: J-fraction approximations
zbMATH Keywords: Poisson random variates
author: C. David Kemp
describes a project that uses: IMSL Numerical Libraries
MaRDI profile type: Publication
cites work: Computer Generation of Poisson Deviates from Modified Normal Distributions
cites work: Q3723577
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cites work: On the Alias Method for Generating Random Variables from a Discrete Distribution
description: scientific article; zbMATH DE number 4151692