A new bivariate beta distribution

Saralees Nadarajah; Shou Hsing Shih; Daya K. Nagar

doi:10.1080/02331888.2016.1240681

A new bivariate beta distribution

Saralees Nadarajah^*, Shou Hsing Shih, Daya K. Nagar

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

A new bivariate beta distribution capable of providing better fits than all its competitors is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure. Applications to six bivariate data sets are illustrated.

Original language	English
Pages (from-to)	455-474
Number of pages	20
Journal	Statistics
Volume	51
Issue number	2
Early online date	5 Oct 2016
DOIs	https://doi.org/10.1080/02331888.2016.1240681
Publication status	Published - 2017

Keywords

Estimation
pollen count
product moments

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10.1080/02331888.2016.1240681

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title = "A new bivariate beta distribution",

abstract = "A new bivariate beta distribution capable of providing better fits than all its competitors is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure. Applications to six bivariate data sets are illustrated.",

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AB - A new bivariate beta distribution capable of providing better fits than all its competitors is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure. Applications to six bivariate data sets are illustrated.

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KW - product moments

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A new bivariate beta distribution

Abstract

Keywords

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