Hanan Rabaya | King Faisal University (original) (raw)

Papers by Hanan Rabaya

Research paper thumbnail of Tampered Random Variable Analysis in Step-Stress Testing: Modeling, Inference, and Applications

Mathematics, Apr 20, 2024

Research paper thumbnail of Analysis of a new jointly hybrid censored Rayleigh populations

Research paper thumbnail of Evaluating the Discrete Generalized Rayleigh Distribution: Statistical Inferences and Applications to Real Data Analysis

Research paper thumbnail of Investigating the Lifetime Performance Index under Ishita Distribution Based on Progressive Type II Censored Data with Applications

Research paper thumbnail of Optimizing analgesic pain relief time analysis through Bayesian and non-Bayesian approaches to new right truncated Fréchet-inverted Weibull distribution

AIMS Mathematics

This research introduces a novel right-truncated distribution, termed the right truncated Fréchet... more This research introduces a novel right-truncated distribution, termed the right truncated Fréchet-inverted Weibull distribution, and elucidates its mathematical properties including density, cumulative, survival and hazard functions. Various statistical attributes such as moments, quantile, mode and moment-generating functions are explored. These properties indicate the efficiency in modeling pain relief time for patients and the number of recoveries of Leukemia patients. Furthermore, estimation techniques, including maximum likelihood and Bayesian methods, are applied to progressive type-Ⅱ right-censored samples to derive parameter estimation of the proposed distribution. Asymptotic properties are employed to approximate confidence intervals for both reliability and hazard functions. Bayesian estimates are refined using both symmetric and asymmetric loss functions. The suitability of the proposed estimation methodologies is validated through simulation studies. The theoretical fram...

Research paper thumbnail of A new generalization of the Pareto distribution and its applications

Statistics in Transition New Series, 2020

Research paper thumbnail of On discrete generalization of the inverse exponential distribution: Properties, characterizations and applications

ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH

Research paper thumbnail of Using merton jump diffusion model to analyze the response of Jakarta Islamic index stock prices during Covid-19 pandemic

ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH

Research paper thumbnail of The Efficiency of Hazard Rate Preservation Method for Generating Discrete Rayleigh–Lindley Distribution

Mathematics, Apr 22, 2024

Research paper thumbnail of On Statistical Inference of Generalized Pareto Distribution with Jointly Progressive Censored Samples with Binomial Removal

Mathematical Problems in Engineering, Apr 21, 2023

Research paper thumbnail of On suitability of modified Weibull extension distribution in modeling product lifetimes and reliability

Advances in Mechanical Engineering

The Weibull distribution (WD) is an important lifetime model. Due to its prime importance in mode... more The Weibull distribution (WD) is an important lifetime model. Due to its prime importance in modeling life data, many researchers have proposed different modifications of WD. One of the most recent modifications of WD is Modified Weibull Extension distribution (MWEM). The MWEM has been shown better in modeling lifetime data as compared to WD. However it comparison with other modifications of WD, in modeling product lifetimes and reliability, is missing in the current literature. We have attempted to bridge up this gap. The Bayesian methods have been proposed for the analysis under non-informative (uniform) and informative (gamma) priors. Since the Bayes estimates for the model parameters were not available in closed form, the Lindley’s approximation (LA) has been used for numerical solutions. Based on detailed simulation study and real life analysis, it has been concluded that Bayesian methods performed better as compared to maximum likelihood estimates (MLE) in estimating the model...

Research paper thumbnail of Progressive censoring schemes for marshall-olkin pareto distribution with applications: Estimation and prediction

PLOS ONE

In this paper two prediction methods are used to predict the non-observed (censored) units under ... more In this paper two prediction methods are used to predict the non-observed (censored) units under progressive Type-II censored samples. The lifetimes of the units follow Marshall-Olkin Pareto distribution. We observe the posterior predictive density of the non-observed units and construct predictive intervals as well. Furthermore, we provide inference on the unknown parameters of the Marshall-Olkin model, so we observe point and interval estimation by using maximum likelihood and Bayesian estimation methods. Bayes estimation methods are obtained under quadratic loss function. EM algorithm is used to obtain numerical values of the Maximum likelihood method and Gibbs and the Monte Carlo Markov chain techniques are utilized for Bayesian calculations. A simulation study is performed to evaluate the performance of the estimators with respect to the mean square errors and the biases. Finally, we find the best prediction method by implementing a real data example under progressive Type-II c...

Research paper thumbnail of Investigating the Relationship between Processor and Memory Reliability in Data Science: A Bivariate Model Approach

Mathematics

Modeling the failure times of processors and memories in computers is crucial for ensuring the re... more Modeling the failure times of processors and memories in computers is crucial for ensuring the reliability and robustness of data science workflows. By understanding the failure characteristics of the hardware components, data scientists can develop strategies to mitigate the impact of failures on their computations, and design systems that are more fault-tolerant and resilient. In particular, failure time modeling allows data scientists to predict the likelihood and frequency of hardware failures, which can help inform decisions about system design and resource allocation. In this paper, we aimed to model the failure times of processors and memories of computers; this was performed by formulating a new type of bivariate model using the copula function. The modified extended exponential distribution is the suggested lifetime of the experimental units. It was shown that the new bivariate model has many important properties, which are presented in this work. The inferential statistics...

Research paper thumbnail of Investigating the Relationship between Processor and Memory Reliability in Data Science: A Bivariate Model Approach

Mathematics, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of The Reliability of Stored Water behind Dams Using the Multi-Component Stress-Strength System

Symmetry

Dams are essential infrastructure for managing water resources and providing entry to clean water... more Dams are essential infrastructure for managing water resources and providing entry to clean water for human needs. However, the construction and maintenance of dams require careful consideration of their reliability and safety, specifically in the event of extreme weather conditions such as heavy rainfall or flooding. In this study, the stress-strength model provides a useful framework for evaluating the reliability of dams and their ability to cope with external stresses such as water pressure, earthquake activity, and erosion. The Shasta reservoir in the United States is a prime example of a dam that requires regular assessment of its reliability to guarantee the safety of communities and infrastructure. The Gumbel Type II distribution has been suggested as a suitable model for fitting the collected data on the stress and strength of the reservoir behind the Shasta dam. Both classical and Bayesian approaches have been used to estimate the reliability function under the multi-compo...

Research paper thumbnail of Statistical Analysis of Alpha Power Inverse Weibull Distribution under Hybrid Censored Scheme with Applications to Ball Bearings Technology and Biomedical Data

Symmetry

Applications in medical technology have a massive contribution to the treatment of patients. One ... more Applications in medical technology have a massive contribution to the treatment of patients. One of the attractive tools is ball bearings. These balls support the load of the application as well as minimize friction between the surfaces. If a heavy load is applied to a ball bearing, there is the risk that the balls may be damaged and cause the bearing to fail earlier. Hence, we aim to study the model of the failure times of ball bearings. A hybrid Type-II censoring scheme is recommended to minimize the experimental time and cost where the components are following alpha power inverse Weibull distribution. A ball bearing is one example; the other is the resistance of guinea pigs exposed to dosages of virulent tubercle bacilli. We use different estimation methods to obtain point and interval estimates of the unknown parameters of the distribution; consequently, estimating statistical functions such as the hazard rate and the survival functions are observed. The maximum likelihood metho...

Research paper thumbnail of On Unit Exponential Pareto Distribution for Modeling the Recovery Rate of COVID-19

Processes

In 2019, a new lethal and mutant virus (COVID-19) spread around the world, causing the deaths of ... more In 2019, a new lethal and mutant virus (COVID-19) spread around the world, causing the deaths of millions of people. COVID-19 demonstrates that scientists are involved in significant research efforts to face bacteria with less effort than that dedicated to viruses. Since then, engineers and bio-materials scientists have been trying to develop antiviral research and find a suitable effective medication. Strategies and opportunities for interference diagnostics, treatment strategies, and predicting future factors became mandatory. From a statistical point of view, estimating and modelling these factors play an important role in preventing future viral epidemics. In this article, modelling the recovery rate of COVID-19 is investigated through a new distribution which is called the unit exponential Pareto distribution. The new continuous distribution with three parameters displays a prominent level of flexibility to model decreasing, symmetric, and asymmetric data with a monotone failur...

Research paper thumbnail of Generating Optimal Discrete Analogue of the Generalized Pareto Distribution under Bayesian Inference with Applications

Symmetry

This paper studies three discretization methods to formulate discrete analogues of the well-known... more This paper studies three discretization methods to formulate discrete analogues of the well-known continuous generalized Pareto distribution. The generalized Pareto distribution provides a wide variety of probability spaces, which support threshold exceedances, and hence, it is suitable for modeling many failure time issues. Bayesian inference is applied to estimate the discrete models with different symmetric and asymmetric loss functions. The symmetric loss function being used is the squared error loss function, while the two asymmetric loss functions are the linear exponential and general entropy loss functions. A detailed simulation analysis was performed to compare the performance of the Bayesian estimation using the proposed loss functions. In addition, the applicability of the optimal discrete generalized Pareto distribution was compared with other discrete distributions. The comparison was based on different goodness-of-fit criteria. The results of the study reveal that the ...

Research paper thumbnail of Modeling of COVID-19 vaccination rate using odd Lomax inverted Nadarajah-Haghighi distribution

PLOS ONE

Since the spread of COVID-19 pandemic in early 2020, modeling the related factors became mandator... more Since the spread of COVID-19 pandemic in early 2020, modeling the related factors became mandatory, requiring new families of statistical distributions to be formulated. In the present paper we are interested in modeling the vaccination rate in some African countries. The recorded data in these countries show less vaccination rate, which will affect the spread of new active cases and will increase the mortality rate. A new extension of the inverted Nadarajah-Haghighi distribution is considered, which has four parameters and is obtained by combining the inverted Nadarajah-Haghighi distribution and the odd Lomax-G family. The proposed distribution is called the odd Lomax inverted Nadarajah-Haghighi (OLINH) distribution. This distribution owns many virtuous characteristics and attractive statistical properties, such as, the simple linear representation of density function, the flexibility of the hazard rate curve and the odd ratio of failure, in addition to other properties related to ...

Research paper thumbnail of A comparative inference on reliability estimation for a multi-component stress-strength model under power Lomax distribution with applications

AIMS Mathematics

In this article, reliability estimation for a system of multi-component stress-strength model is ... more In this article, reliability estimation for a system of multi-component stress-strength model is considered. Working under progressively censored samples is of great advantage over complete and usual censoring samples, therefore Type-II right progressive censored sample is selected. The lifetime of the components and the stress and strength components are following the power Lomax distribution. Consequently, the problem of point and interval estimation has been studied from different points of view. The maximum likelihood estimate and the maximum product spacing of reliability are evaluated. Also approximate confidence intervals are constructed using the Fisher information matrix. For the traditional methods, bootstrap confidence intervals are calculated. Bayesian estimation is obtained under the squared error and linear-exponential loss functions, where the numerical techniques such as Newton-Raphson and the Markov Chain Monte Carlo algorithm are implemented. For dependability, the...

Research paper thumbnail of Tampered Random Variable Analysis in Step-Stress Testing: Modeling, Inference, and Applications

Mathematics, Apr 20, 2024

Research paper thumbnail of Analysis of a new jointly hybrid censored Rayleigh populations

Research paper thumbnail of Evaluating the Discrete Generalized Rayleigh Distribution: Statistical Inferences and Applications to Real Data Analysis

Research paper thumbnail of Investigating the Lifetime Performance Index under Ishita Distribution Based on Progressive Type II Censored Data with Applications

Research paper thumbnail of Optimizing analgesic pain relief time analysis through Bayesian and non-Bayesian approaches to new right truncated Fréchet-inverted Weibull distribution

AIMS Mathematics

This research introduces a novel right-truncated distribution, termed the right truncated Fréchet... more This research introduces a novel right-truncated distribution, termed the right truncated Fréchet-inverted Weibull distribution, and elucidates its mathematical properties including density, cumulative, survival and hazard functions. Various statistical attributes such as moments, quantile, mode and moment-generating functions are explored. These properties indicate the efficiency in modeling pain relief time for patients and the number of recoveries of Leukemia patients. Furthermore, estimation techniques, including maximum likelihood and Bayesian methods, are applied to progressive type-Ⅱ right-censored samples to derive parameter estimation of the proposed distribution. Asymptotic properties are employed to approximate confidence intervals for both reliability and hazard functions. Bayesian estimates are refined using both symmetric and asymmetric loss functions. The suitability of the proposed estimation methodologies is validated through simulation studies. The theoretical fram...

Research paper thumbnail of A new generalization of the Pareto distribution and its applications

Statistics in Transition New Series, 2020

Research paper thumbnail of On discrete generalization of the inverse exponential distribution: Properties, characterizations and applications

ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH

Research paper thumbnail of Using merton jump diffusion model to analyze the response of Jakarta Islamic index stock prices during Covid-19 pandemic

ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH

Research paper thumbnail of The Efficiency of Hazard Rate Preservation Method for Generating Discrete Rayleigh–Lindley Distribution

Mathematics, Apr 22, 2024

Research paper thumbnail of On Statistical Inference of Generalized Pareto Distribution with Jointly Progressive Censored Samples with Binomial Removal

Mathematical Problems in Engineering, Apr 21, 2023

Research paper thumbnail of On suitability of modified Weibull extension distribution in modeling product lifetimes and reliability

Advances in Mechanical Engineering

The Weibull distribution (WD) is an important lifetime model. Due to its prime importance in mode... more The Weibull distribution (WD) is an important lifetime model. Due to its prime importance in modeling life data, many researchers have proposed different modifications of WD. One of the most recent modifications of WD is Modified Weibull Extension distribution (MWEM). The MWEM has been shown better in modeling lifetime data as compared to WD. However it comparison with other modifications of WD, in modeling product lifetimes and reliability, is missing in the current literature. We have attempted to bridge up this gap. The Bayesian methods have been proposed for the analysis under non-informative (uniform) and informative (gamma) priors. Since the Bayes estimates for the model parameters were not available in closed form, the Lindley’s approximation (LA) has been used for numerical solutions. Based on detailed simulation study and real life analysis, it has been concluded that Bayesian methods performed better as compared to maximum likelihood estimates (MLE) in estimating the model...

Research paper thumbnail of Progressive censoring schemes for marshall-olkin pareto distribution with applications: Estimation and prediction

PLOS ONE

In this paper two prediction methods are used to predict the non-observed (censored) units under ... more In this paper two prediction methods are used to predict the non-observed (censored) units under progressive Type-II censored samples. The lifetimes of the units follow Marshall-Olkin Pareto distribution. We observe the posterior predictive density of the non-observed units and construct predictive intervals as well. Furthermore, we provide inference on the unknown parameters of the Marshall-Olkin model, so we observe point and interval estimation by using maximum likelihood and Bayesian estimation methods. Bayes estimation methods are obtained under quadratic loss function. EM algorithm is used to obtain numerical values of the Maximum likelihood method and Gibbs and the Monte Carlo Markov chain techniques are utilized for Bayesian calculations. A simulation study is performed to evaluate the performance of the estimators with respect to the mean square errors and the biases. Finally, we find the best prediction method by implementing a real data example under progressive Type-II c...

Research paper thumbnail of Investigating the Relationship between Processor and Memory Reliability in Data Science: A Bivariate Model Approach

Mathematics

Modeling the failure times of processors and memories in computers is crucial for ensuring the re... more Modeling the failure times of processors and memories in computers is crucial for ensuring the reliability and robustness of data science workflows. By understanding the failure characteristics of the hardware components, data scientists can develop strategies to mitigate the impact of failures on their computations, and design systems that are more fault-tolerant and resilient. In particular, failure time modeling allows data scientists to predict the likelihood and frequency of hardware failures, which can help inform decisions about system design and resource allocation. In this paper, we aimed to model the failure times of processors and memories of computers; this was performed by formulating a new type of bivariate model using the copula function. The modified extended exponential distribution is the suggested lifetime of the experimental units. It was shown that the new bivariate model has many important properties, which are presented in this work. The inferential statistics...

Research paper thumbnail of Investigating the Relationship between Processor and Memory Reliability in Data Science: A Bivariate Model Approach

Mathematics, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of The Reliability of Stored Water behind Dams Using the Multi-Component Stress-Strength System

Symmetry

Dams are essential infrastructure for managing water resources and providing entry to clean water... more Dams are essential infrastructure for managing water resources and providing entry to clean water for human needs. However, the construction and maintenance of dams require careful consideration of their reliability and safety, specifically in the event of extreme weather conditions such as heavy rainfall or flooding. In this study, the stress-strength model provides a useful framework for evaluating the reliability of dams and their ability to cope with external stresses such as water pressure, earthquake activity, and erosion. The Shasta reservoir in the United States is a prime example of a dam that requires regular assessment of its reliability to guarantee the safety of communities and infrastructure. The Gumbel Type II distribution has been suggested as a suitable model for fitting the collected data on the stress and strength of the reservoir behind the Shasta dam. Both classical and Bayesian approaches have been used to estimate the reliability function under the multi-compo...

Research paper thumbnail of Statistical Analysis of Alpha Power Inverse Weibull Distribution under Hybrid Censored Scheme with Applications to Ball Bearings Technology and Biomedical Data

Symmetry

Applications in medical technology have a massive contribution to the treatment of patients. One ... more Applications in medical technology have a massive contribution to the treatment of patients. One of the attractive tools is ball bearings. These balls support the load of the application as well as minimize friction between the surfaces. If a heavy load is applied to a ball bearing, there is the risk that the balls may be damaged and cause the bearing to fail earlier. Hence, we aim to study the model of the failure times of ball bearings. A hybrid Type-II censoring scheme is recommended to minimize the experimental time and cost where the components are following alpha power inverse Weibull distribution. A ball bearing is one example; the other is the resistance of guinea pigs exposed to dosages of virulent tubercle bacilli. We use different estimation methods to obtain point and interval estimates of the unknown parameters of the distribution; consequently, estimating statistical functions such as the hazard rate and the survival functions are observed. The maximum likelihood metho...

Research paper thumbnail of On Unit Exponential Pareto Distribution for Modeling the Recovery Rate of COVID-19

Processes

In 2019, a new lethal and mutant virus (COVID-19) spread around the world, causing the deaths of ... more In 2019, a new lethal and mutant virus (COVID-19) spread around the world, causing the deaths of millions of people. COVID-19 demonstrates that scientists are involved in significant research efforts to face bacteria with less effort than that dedicated to viruses. Since then, engineers and bio-materials scientists have been trying to develop antiviral research and find a suitable effective medication. Strategies and opportunities for interference diagnostics, treatment strategies, and predicting future factors became mandatory. From a statistical point of view, estimating and modelling these factors play an important role in preventing future viral epidemics. In this article, modelling the recovery rate of COVID-19 is investigated through a new distribution which is called the unit exponential Pareto distribution. The new continuous distribution with three parameters displays a prominent level of flexibility to model decreasing, symmetric, and asymmetric data with a monotone failur...

Research paper thumbnail of Generating Optimal Discrete Analogue of the Generalized Pareto Distribution under Bayesian Inference with Applications

Symmetry

This paper studies three discretization methods to formulate discrete analogues of the well-known... more This paper studies three discretization methods to formulate discrete analogues of the well-known continuous generalized Pareto distribution. The generalized Pareto distribution provides a wide variety of probability spaces, which support threshold exceedances, and hence, it is suitable for modeling many failure time issues. Bayesian inference is applied to estimate the discrete models with different symmetric and asymmetric loss functions. The symmetric loss function being used is the squared error loss function, while the two asymmetric loss functions are the linear exponential and general entropy loss functions. A detailed simulation analysis was performed to compare the performance of the Bayesian estimation using the proposed loss functions. In addition, the applicability of the optimal discrete generalized Pareto distribution was compared with other discrete distributions. The comparison was based on different goodness-of-fit criteria. The results of the study reveal that the ...

Research paper thumbnail of Modeling of COVID-19 vaccination rate using odd Lomax inverted Nadarajah-Haghighi distribution

PLOS ONE

Since the spread of COVID-19 pandemic in early 2020, modeling the related factors became mandator... more Since the spread of COVID-19 pandemic in early 2020, modeling the related factors became mandatory, requiring new families of statistical distributions to be formulated. In the present paper we are interested in modeling the vaccination rate in some African countries. The recorded data in these countries show less vaccination rate, which will affect the spread of new active cases and will increase the mortality rate. A new extension of the inverted Nadarajah-Haghighi distribution is considered, which has four parameters and is obtained by combining the inverted Nadarajah-Haghighi distribution and the odd Lomax-G family. The proposed distribution is called the odd Lomax inverted Nadarajah-Haghighi (OLINH) distribution. This distribution owns many virtuous characteristics and attractive statistical properties, such as, the simple linear representation of density function, the flexibility of the hazard rate curve and the odd ratio of failure, in addition to other properties related to ...

Research paper thumbnail of A comparative inference on reliability estimation for a multi-component stress-strength model under power Lomax distribution with applications

AIMS Mathematics

In this article, reliability estimation for a system of multi-component stress-strength model is ... more In this article, reliability estimation for a system of multi-component stress-strength model is considered. Working under progressively censored samples is of great advantage over complete and usual censoring samples, therefore Type-II right progressive censored sample is selected. The lifetime of the components and the stress and strength components are following the power Lomax distribution. Consequently, the problem of point and interval estimation has been studied from different points of view. The maximum likelihood estimate and the maximum product spacing of reliability are evaluated. Also approximate confidence intervals are constructed using the Fisher information matrix. For the traditional methods, bootstrap confidence intervals are calculated. Bayesian estimation is obtained under the squared error and linear-exponential loss functions, where the numerical techniques such as Newton-Raphson and the Markov Chain Monte Carlo algorithm are implemented. For dependability, the...

Research paper thumbnail of The Reliability of Stored Water Behind Dams Using the Multi-Component Stress-Strength System

Symmetry , 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY