1983•ACM SIGSIM Simulation DigestOpen access

The bivariate beta distribution

James H. Macomber, Buddy L. Myers

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Abstract

The bivariate and multivariate beta distributions may provide appropriate stochastic models for a number of processes, particularly those involving random proportions. Researchers may therefore find it necessary to estimate the parameters of such distributions or generate Monte Carlo samples with known parameter values. Two possible generating technique for beta bivariates are presented and compared in this paper. Estimating equations for the three parameters of the bivariate beta distribution are presented. These use the method of moments, the only tractable estimating techniques and an analysis of their properties is also presented.This paper focuses on the bivariate beta distribution, but a user of a higher-dimensioned beta model will be able to make use of the discussion herein to provide assistance in determining many of the properties of such a model.

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What this paper is about

The bivariate and multivariate beta distributions may provide appropriate stochastic models for a number of processes, particularly those involving random proportions. Researchers may therefore find it necessary to estimate the parameters of such distributions or generate Monte Carlo samples with known parameter values. Two possible generating technique for beta bivariates are presented and compared in this paper. Estimating equations for the three parameters of the bivariate beta distribution are presented. These use the method of moments, the only tractable estimating techniques and an analysis of their properties is also presented.This paper focuses on the bivariate beta distribution, but a user of a higher-dimensioned beta model will be able to make use of the discussion herein to provide assistance in determining many of the properties of such a model.

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Available abstract

The bivariate and multivariate beta distributions may provide appropriate stochastic models for a number of processes, particularly those involving random proportions. Researchers may therefore find it necessary to estimate the parameters of such distributions or generate Monte Carlo samples with known parameter values. Two possible generating technique for beta bivariates are presented and compared in this paper. Estimating equations for the three parameters of the bivariate beta distribution are presented. These use the method of moments, the only tractable estimating techniques and an analysis of their properties is also presented.This paper focuses on the bivariate beta distribution, but a user of a higher-dimensioned beta model will be able to make use of the discussion herein to provide assistance in determining many of the properties of such a model.

Key concepts: Bivariate analysis, Beta distribution, Computer science, BETA (programming language), Monte Carlo method, Distribution (mathematics), Multivariate statistics, Multivariate normal distribution

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