A New Class of Bivariate Distributions: Properties, Estimation, and Modeling

The development of bivariate distributions is a challenging area of research, and a novel class of bivariate distributions is proposed in this paper. Certain useful mathematical characteristics of the proposed class of bivariate distributions are explored in general. These properties include the joint and conditional and joint survival function moments and measures of dependence. The parameters of the proposed class of distributions are estimated using the maximum likelihood method of estimation. A multivariate version of the proposed class is also proposed, and some necessary properties are discussed. The multivariate dependence measures are obtained for the proposed multivariate class of distributions. A new bivariate power function distribution is proposed using the power function distribution as a baseline distribution in the proposed bivariate class. Some useful properties of the proposed bivariate distribution are studied. The parameters of the proposed bivariate distribution are estimated using the maximum likelihood method. An extensive simulation study has been conducted to see the performance of the estimation method. The new bivariate power function distribution is used to model some real data.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2024-12-22
DOI
https://doi.org/10.3390/math12244021
Citations
2
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
1.42

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A New Class of Bivariate Distributions: Properties, Estimation, and Modeling

Muhammad Shahbaz, Jumanah Ahmed Darwish, Saman Hanif Shahbaz
2 citations
Mathematics
Statistical Distribution Estimation and Applications
1.42
article

A New Class of Bivariate Distributions: Properties, Estimation, and Modeling

Muhammad Shahbaz, Jumanah Ahmed Darwish, Saman Hanif Shahbaz
article en
2 citations

Abstract

The development of bivariate distributions is a challenging area of research, and a novel class of bivariate distributions is proposed in this paper. Certain useful mathematical characteristics of the proposed class of bivariate distributions are explored in general. These properties include the joint and conditional and joint survival function moments and measures of dependence. The parameters of the proposed class of distributions are estimated using the maximum likelihood method of estimation. A multivariate version of the proposed class is also proposed, and some necessary properties are discussed. The multivariate dependence measures are obtained for the proposed multivariate class of distributions. A new bivariate power function distribution is proposed using the power function distribution as a baseline distribution in the proposed bivariate class. Some useful properties of the proposed bivariate distribution are studied. The parameters of the proposed bivariate distribution are estimated using the maximum likelihood method. An extensive simulation study has been conducted to see the performance of the estimation method. The new bivariate power function distribution is used to model some real data.

MathematicsVol. 12(24)
King Abdulaziz University (SA), University of Jeddah (SA)
University of Jeddah
Openalex Percentile: Top 16%
Statistical Distribution Estimation and Applications
1.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.