Mean and variance of ratios of proportions from categories of a multinomial distribution

Abstract Ratio distribution is a probability distribution representing the ratio of two random variables, each usually having a known distribution. Currently, there are results when the random variables in the ratio follow (not necessarily the same) Gaussian, Cauchy, binomial or uniform distribution...

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Main Authors: Frantisek Duris, Juraj Gazdarica, Iveta Gazdaricova, Lucia Strieskova, Jaroslav Budis, Jan Turna, Tomas Szemes
Format: Article
Language:English
Published: SpringerOpen 2018-01-01
Series:Journal of Statistical Distributions and Applications
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40488-018-0083-x
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spelling doaj-7be8ed3db6bf49b2a3d08f6ee34bae3a2020-11-24T21:39:53ZengSpringerOpenJournal of Statistical Distributions and Applications2195-58322018-01-015112010.1186/s40488-018-0083-xMean and variance of ratios of proportions from categories of a multinomial distributionFrantisek Duris0Juraj Gazdarica1Iveta Gazdaricova2Lucia Strieskova3Jaroslav Budis4Jan Turna5Tomas Szemes6Geneton s.r.o.Comenius University, Faculty of Natural SciencesComenius University, Faculty of Natural SciencesComenius University, Faculty of Natural SciencesComenius University Faculty of Mathematics, Physics and InformaticsComenius University, Science ParkGeneton s.r.o.Abstract Ratio distribution is a probability distribution representing the ratio of two random variables, each usually having a known distribution. Currently, there are results when the random variables in the ratio follow (not necessarily the same) Gaussian, Cauchy, binomial or uniform distributions. In this paper we consider a case, where the random variables in the ratio are joint binomial components of a multinomial distribution. We derived formulae for mean and variance of this ratio distribution using a simple Taylor-series approach and also a more complex approach which uses a slight modification of the original ratio. We showed that the more complex approach yields better results with simulated data. The presented results can be directly applied in the computation of confidence intervals for ratios of multinomial proportions. AMS Subject Classification: 62E20http://link.springer.com/article/10.1186/s40488-018-0083-xMultinomial distributionRatio distributionMeanVariance
collection DOAJ
language English
format Article
sources DOAJ
author Frantisek Duris
Juraj Gazdarica
Iveta Gazdaricova
Lucia Strieskova
Jaroslav Budis
Jan Turna
Tomas Szemes
spellingShingle Frantisek Duris
Juraj Gazdarica
Iveta Gazdaricova
Lucia Strieskova
Jaroslav Budis
Jan Turna
Tomas Szemes
Mean and variance of ratios of proportions from categories of a multinomial distribution
Journal of Statistical Distributions and Applications
Multinomial distribution
Ratio distribution
Mean
Variance
author_facet Frantisek Duris
Juraj Gazdarica
Iveta Gazdaricova
Lucia Strieskova
Jaroslav Budis
Jan Turna
Tomas Szemes
author_sort Frantisek Duris
title Mean and variance of ratios of proportions from categories of a multinomial distribution
title_short Mean and variance of ratios of proportions from categories of a multinomial distribution
title_full Mean and variance of ratios of proportions from categories of a multinomial distribution
title_fullStr Mean and variance of ratios of proportions from categories of a multinomial distribution
title_full_unstemmed Mean and variance of ratios of proportions from categories of a multinomial distribution
title_sort mean and variance of ratios of proportions from categories of a multinomial distribution
publisher SpringerOpen
series Journal of Statistical Distributions and Applications
issn 2195-5832
publishDate 2018-01-01
description Abstract Ratio distribution is a probability distribution representing the ratio of two random variables, each usually having a known distribution. Currently, there are results when the random variables in the ratio follow (not necessarily the same) Gaussian, Cauchy, binomial or uniform distributions. In this paper we consider a case, where the random variables in the ratio are joint binomial components of a multinomial distribution. We derived formulae for mean and variance of this ratio distribution using a simple Taylor-series approach and also a more complex approach which uses a slight modification of the original ratio. We showed that the more complex approach yields better results with simulated data. The presented results can be directly applied in the computation of confidence intervals for ratios of multinomial proportions. AMS Subject Classification: 62E20
topic Multinomial distribution
Ratio distribution
Mean
Variance
url http://link.springer.com/article/10.1186/s40488-018-0083-x
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