Computer generation of Poisson deviates from modified normal distributions

Joachim Ahrens, Ulrich Dieter

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Abstract

Samples from Poisson distributions of mean μ 10 are generated by truncating suitable normal deviates and applymg a correction with low probability, For μ < 10, mversion is substituted. The method is accurate and it can cope with changing parameters μ. Using efficient subprograms for generating uniform, exponential, and normal deviates, the new algorithm is much faster than all competing methods.
Original languageEnglish
Pages (from-to)163-179
JournalACM Transactions on Mathematical Software
Volume8
Issue number2
DOIs
Publication statusPublished - 1982

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  • Random Number Generation

    Dieter, U. & Stadlober, E.

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    Project: Research area

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