Cambanis-type Bivariate Uniform Distribution: Properties and Moment Estimation

The families of distributions are crucial in statistical modeling, offering a versatile foundation for a variety of applications. The development of bivariate distributions with specific marginal distributions and correlation coefficients is of considerable interest due to its wide-ranging relevance...

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Bibliographic Details
Main Authors: Rohan Dilip Koshti, Kirtee Kiran Kamalja
Format: Article
Language:English
Published: The Scientific Association for Studies and Applied Research 2024-04-01
Series:Computational Journal of Mathematical and Statistical Sciences
Subjects:
Online Access:https://cjmss.journals.ekb.eg/article_331792.html
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Summary:The families of distributions are crucial in statistical modeling, offering a versatile foundation for a variety of applications. The development of bivariate distributions with specific marginal distributions and correlation coefficients is of considerable interest due to its wide-ranging relevance in real-world situations. The range of correlation between variables is an important characterization of the family. The variety of methods of construction of bivariate/multivariate distributions are developed in the literature. The Cambanis family is an important class of multivariate distributions with a wide range of correlation than the traditional families. In this paper, we consider a Cambanis-type bivariate uniform distribution and develop key statistical properties of the Cambanis-type bivariate uniform distribution. We obtain moment estimators of parameters for Cambanis-type bivariate uniform distribution. To evaluate the performance of the estimators, we develop an algorithm to simulate samples from the Cambanis-type bivariate uniform distribution and implement it in the R software. We perform a simulation study to present the performance of moment estimator.
ISSN:2974-3435
2974-3443