Bivariate power Lomax distribution with medical applications

Qura, Maha E.; Fayomi, Aisha; Kilai, Mutua; Almetwally, Ehab M.

doi:10.1371/journal.pone.0282581

Cited by 15 publications

(4 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The RVs T and Z represent the mean serum creatinine levels (SrCr) and the mean duration of diabetes, respectively. This data set, which presents information from 19 patients, can be found in [41,42]. We fit the exponential distribution to Z and T, with the scale parameters θ 1 and θ 2 , separately.…”

Section: Application To Diabetic Nephropathy Datamentioning

confidence: 99%

Fisher Information, Asymptotic Behavior, and Applications for Generalized Order Statistics and Their Concomitants Based on the Sarmanov Family

Abd Elgawad,

Barakat,

Husseiny

et al. 2023

Axioms

View full text Add to dashboard Cite

In this paper, the Fisher information (FI), relevant to m-generalized order statistics (m-GOSs) and their concomitants of the shape-parameter of the Sarmanov family of bivariate distributions, is investigated. In addition, we study the concomitants of m-GOSs from this family. Furthermore, we look at how those concomitants were distributed collectively. The FI contained in the scale and shape parameters of the exponential and power function distributions, respectively, in concomitants of m-GOSs is obtained. A study of the asymptotic behavior of the concomitants of ordinary order statistics is also provided. Some versatile applications for this study are offered. As a final step, we examined a bivariate real-world data set for illustrative purposes.

show abstract

Section: Application To Diabetic Nephropathy Datamentioning

confidence: 99%

Fisher Information, Asymptotic Behavior, and Applications for Generalized Order Statistics and Their Concomitants Based on the Sarmanov Family

Abd Elgawad,

Barakat,

Husseiny

et al. 2023

Axioms

View full text Add to dashboard Cite

show abstract

“…Several studies have discussed bivariate distributions based on copulas. These include the works of Elgohari and Yousof [38], Hamed et al [39], Aboraya et al [40], El-Sherpieny et al [41], El-Sherpieny et al [42], El-Sherpieny et al [43], Almetwally et al [44], El-Sherpieny et al [45], Muhammed et al [46], Abulebda et al [47], Hassan et al [48], Zhao et al [49], and Qura et al [50].…”

Section: Introductionmentioning

confidence: 99%

Bivariate Exponentiated Lomax Distribution Based on Marshall-olkin Method With a Real-life Application

Kalantan,

EL-Helbawy,

AL-Dayian

et al. 2024

Preprint

View full text Add to dashboard Cite

This paper focuses on applying the Marshall-Olkin approach to generate a new bivariate distribution. The distribution is called the bivariate exponentiated Lomax distribution, and its marginal distribution is the exponentiated Lomax distribution. Numerous attributes are examined, including the joint reliability and hazard functions, the bivariate probability density function, and its marginal. The joint probability density function and joint cumulative distribution function can be stated analytically. Different contour plots of the joint probability density function, joint reliability, joint hazard rate functions of the bivariate exponentiated Lomax distribution are given. The unknown parameters, reliability, and hazard rate functions of the bivariate exponentiated Lomax distribution are estimated using the maximum likelihood method. Also, Bayesian technique is applied to derive the Bayes estimators, reliability and hazard rate functions of the bivariate exponentiated Lomax distribution. In addition, maximum likelihood and Bayesian two-sample prediction is considered to predict a future observation from a future sample of the bivariate exponentiated Lomax distribution. Finally, a numerical illustration is presented, including a simulation study to investigate the theoretical findings derived in this paper of the maximum likelihood and Bayesian estimation. Also, a simulation study is provided to evaluate the theoretical outcomes and performance of the maximum likelihood and Bayesian predictors. Furthermore, the real data set used in this paper is the scoring times from 42 American Football League matches that took place over three consecutive independent weekends in 1986. The results of utilizing the real data approves the practicality and flexibility of the bivariate exponentiated Lomax distribution in real-world situations and that the bivariate exponentiated Lomax distribution is suitable for modeling this bivariate data set. Mathematics Subject Classification: 62F10, 62F15, 62N05, 62E10, 62N0

show abstract

“…Usman and Aliyu [17] proposed a new bivariate Nadarajah-Haghighi distribution using two copula functions: the Gumbel-Barnett and Clayton copula functions. Qura et al [18] introduced a bivariate power Lomax distribution, named BFGMPLx, which is based on Farlie-Gumbel-Morgenstern (FGM) copulas. Fayomi et al [19] presented a novel family of bivariate continuous Lomax generators called the BFGMLG family.…”

Section: Introductionmentioning

confidence: 99%

Advanced Copula-Based Models for Type II Censored Data: Applications in Industrial and Medical Settings

Almetwally,

Fayomi,

Qura

2024

Mathematics

Self Cite

View full text Add to dashboard Cite

Copula models are increasingly recognized for their ability to capture complex dependencies among random variables. In this study, we introduce three innovative bivariate models utilizing copula functions: the XLindley (XL) distribution with Frank, Gumbel, and Clayton copulas. The results highlight the fundamental characteristics and effectiveness of these newly introduced bivariate models. Statistical inference for the distribution parameters is conducted using a Type II censored sampling design. This employs maximum likelihood and Bayesian estimation techniques. Asymptotic and credible confidence intervals are calculated, and numerical analysis is performed using the Markov Chain Monte Carlo method. The proposed methodology’s applicability is illustrated by analyzing several real-world datasets. The initial dataset examines burr formation occurrences and consists of two observation sets. Additionally, the second and third datasets contain medical information. The second dataset focuses on diabetic nephropathy, while the third dataset explores infection and recurrence time among kidney patients.

show abstract

Bivariate power Lomax distribution with medical applications

Cited by 15 publications

References 37 publications

Fisher Information, Asymptotic Behavior, and Applications for Generalized Order Statistics and Their Concomitants Based on the Sarmanov Family

Fisher Information, Asymptotic Behavior, and Applications for Generalized Order Statistics and Their Concomitants Based on the Sarmanov Family

Bivariate Exponentiated Lomax Distribution Based on Marshall-olkin Method With a Real-life Application

Advanced Copula-Based Models for Type II Censored Data: Applications in Industrial and Medical Settings

Contact Info

Product

Resources

About