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Recursive formulas for multinomial probabilities with applications

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  • A. Hayter

Abstract

Recursive formulas are provided for computing probabilities of a multinomial distribution. Firstly, a recursive formula is provided for computing rectangular probabilities which include the cumulative distribution function as a special case. These rectangular probabilities can be used to provide goodness-of-fit tests for the cell probabilities. The probability that a certain cell count is the maximum of all cell counts is also considered, which can be used to assess the probability that the maximum cell count corresponds to the cell with the maximum probability. Finally, a recursive formula is provided for computing the probability that the cell counts satisfy a certain ordering, which can be used to assess the probability that the ordering of the cell counts corresponds to the ordering of the cell probabilities. The computational intensity of these recursive formulas is linear in the number of cells, and they provide opportunities for calculating probabilities that would otherwise be computationally challenging. Some examples of the applications of these formulas are provided. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • A. Hayter, 2014. "Recursive formulas for multinomial probabilities with applications," Computational Statistics, Springer, vol. 29(5), pages 1207-1219, October.
    • Handle: RePEc:spr:compst:v:29:y:2014:i:5:p:1207-1219
    DOI: 10.1007/s00180-014-0487-0
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    References listed on IDEAS

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    1. Ahmad, Ibrahim A., 1985. "On the Poisson approximation of multinomial probabilities," Statistics & Probability Letters, Elsevier, vol. 3(1), pages 55-56, February.
    2. Frey, Jesse, 2012. "Testing for positive evidence of equally likely outcomes," Journal of Multivariate Analysis, Elsevier, vol. 103(1), pages 48-57, January.
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    Cited by:

    1. Sorawit Saengkyongam & Anthony Hayter & Seksan Kiatsupaibul & Wei Liu, 2020. "Efficient computation of the stochastic behavior of partial sum processes," Computational Statistics, Springer, vol. 35(1), pages 343-358, March.
    2. Schaarschmidt, Frank & Gerhard, Daniel & Vogel, Charlotte, 2017. "Simultaneous confidence intervals for comparisons of several multinomial samples," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 65-76.

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