scholarly journals A New Flexible Lifetime Model with Statistical Properties and Applications

2018 ◽  
pp. 881-901
Author(s):  
Mohamed Abo Raya
Keyword(s):  
Survival Times ◽  
New Model ◽  
Proposed Model ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull ◽  
Weibull Models ◽  
Lifetime Model ◽  
Modified Weibull ◽  
The Right ◽  
Better Than

In this article, we introduce a new lifetime model which exhibits the increasing, the decreasing and the bathtub hazard rates. The considerable justification for the practicality of the new lifetime model is depended on the wider use of the exponentiated Weibull and Weibull lifetime models. The new lifetime model can be viewed as a mixture of the exponentiated Weibull distribution. It can also be viewed as a appropriate model for fitting the right skewed, the symmetric, the left skewed and the unimodal data. We prove empirically the importance and flexibility of the new model in modeling two types of lifetime data. The new lifetime model is a superior on the Marshall Olkin extended-Weibull, the Poisson Topp Leone-Weibull, the Burr X Exponentiated-Weibull, the Kumaraswamy-Weibull, the Gamma-Weibull, the Transmuted modified-Weibull, the Weibull-Fréchet, the Beta-Weibull, the Mcdonald-Weibull, the transmuted exponentiated generalized-Weibull, the Kumaraswamy transmuted-Weibull, and the Modified beta-Weibull models so the new model is a good substitutional to these models in modeling the aircraft windshield data. The new lifetime model is much better than the Mcdonald-Weibull, the transmuted linear exponential, the Weibull, the transmuted modified-Weibull, the Modified beta-Weibull,the transmuted additive-Weibull, the exponentiated transmuted generalized Rayleig models in modeling cancer patient data. In modeling the survival times of Guinea pigs data we deduced that the proposed model is much better than the Odd Weibull-Weibull, the Weibull Logarithmic-Weibull and the gamma exponentiated-exponential models. Finally, the new model is a preferable model than the exponentiated-Weibull, the transmuted-Weibull, the Odd Log Logistic-Weibull models, and a good alternate to these models in modeling Glass fibres data.

scholarly journals A New Extremely Flexible Version of the Exponentiated Weibull Model: Theorem and Applications to Reliability and Medical Data Sets

2019 ◽  
pp. 195-215
Author(s):  
Mohamed Abo Raya
Keyword(s):  
Weibull Model ◽  
Hazard Rates ◽  
Data Sets ◽  
Suitable Model ◽  
New Model ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull ◽  
Weibull Models ◽  
Lifetime Model ◽  
New Distribution

In this work, a new lifetime model is introduced and studied. The major justification for the practicality of the new model is based on the wider use of the exponentiated Weibull and Weibull models. We are also motivated to introduce the new lifetime model since it exhibits decreasing, upside down-increasing, constant, increasing-constant and J shaped hazard rates also the density of the new distribution exhibits various important shapes. The new model can be viewed as a mixture of the exponentiated Weibull distribution. It can also be considered as a suitable model for fitting the symmetric, left skewed, right skewed and unimodal data. The importance and flexibility of the new model is illustrated by four read data applications.

scholarly journals The Burr X Exponentiated Weibull Model: Characterizations,Mathematical Properties and Applications to Failure and Survival Times Data

2019 ◽  
pp. 141-160 ◽  
Author(s):  
Mohamed G. Khalil ◽  
G. G. Hamedani ◽  
Haitham M. Yousof
Keyword(s):  
Weibull Model ◽  
Good Alternative ◽  
Likelihood Method ◽  
Model Parameters ◽  
Suitable Model ◽  
Survival Times ◽  
Exponentiated Weibull ◽  
Weibull Models ◽  
Lifetime Model ◽  
The Right

In this article, we introduce a new three-parameter lifetime model called the Burr X exponentiated Weibull model. The major justification for the practicality of the new lifetime model is based on the wider use of the exponentiated Weibull and Weibull models. We are motivated to propose this new lifetime model because it exhibits increasing, decreasing, bathtub, J shaped and constant hazard rates. The new lifetime model can be viewed as a mixture of the exponentiated Weibull distribution. It can also be viewed as a suitable model for fitting the right skewed, symmetric, left skewed and unimodal data. We provide a comprehensive account of some of its statistical properties. Some useful characterization results are presented. The maximum likelihood method is used to estimate the model parameters. We prove empirically the importance and flexibility of the new model in modeling two types of lifetime data. The proposed model is a better fit than the Poisson Topp Leone-Weibull, the Marshall Olkin extended-Weibull, gamma-Weibull , Kumaraswamy-Weibull , Weibull-Fréchet, beta-Weibull, transmuted modified-Weibull, Kumaraswamy transmuted- Weibull, modified beta-Weibull, Mcdonald-Weibull and transmuted exponentiated generalized-Weibull models so it is a good alternative to these models in modeling aircraft windshield data as well as the new lifetime model is much better than the Weibull-Weibull, odd Weibull-Weibull, Weibull Log-Weibull, the gamma exponentiated-exponential and exponential exponential-geometric models so it is a good alternative to these models in modeling the survival times of Guinea pigs. We hope that the new distribution will attract wider applications in reliability, engineering and other areas of research.

scholarly journals A New Flexible Version of the Lomax Distribution with Applications

2018 ◽  
Vol 7 (5) ◽  
pp. 120
Author(s):  
T. H. M. Abouelmagd
Keyword(s):  
Estimation Method ◽  
Good Alternative ◽  
Model Parameters ◽  
Data Sets ◽  
Suitable Model ◽  
Lifetime Data ◽  
New Model ◽  
The Right ◽  
New Distribution ◽  
Better Than

A new version of the Lomax model is introduced andstudied. The major justification for the practicality of the new model isbased on the wider use of the Lomax model. We are also motivated tointroduce the new model since the density of the new distribution exhibitsvarious important shapes such as the unimodal, the right skewed and the leftskewed. The new model can be viewed as a mixture of the exponentiated Lomaxdistribution. It can also be considered as a suitable model for fitting thesymmetric, left skewed, right skewed, and unimodal data sets. The maximumlikelihood estimation method is used to estimate the model parameters. Weprove empirically the importance and flexibility of the new model inmodeling two types of aircraft windshield lifetime data sets. The proposedlifetime model is much better than gamma Lomax, exponentiated Lomax, Lomaxand beta Lomax models so the new distribution is a good alternative to thesemodels in modeling aircraft windshield data.

scholarly journals Statistical Learning of the Worst Regional Smog Extremes with Dynamic Conditional Modeling

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 665
Author(s):  
Lu Deng ◽  
Mengxin Yu ◽  
Zhengjun Zhang
Keyword(s):  
Statistical Learning ◽  
Weather Factors ◽  
Likelihood Principle ◽  
Modeling And Analysis ◽  
Pm 2.5 ◽  
Proposed Model ◽  
Autoregressive Parameter ◽  
Exponentiated Weibull Distribution ◽  
Exponentiated Weibull ◽  
Conditional Maximum

This paper is concerned with the statistical learning of the extreme smog (PM 2.5 ) dynamics of a vast region in China. Differently from classical extreme value modeling approaches, this paper develops a dynamic model of conditional, exponentiated Weibull distribution modeling and analysis of regional smog extremes, particularly for the worst scenarios observed in each day. To gain higher modeling efficiency, weather factors will be introduced in an enhanced model. The proposed model and the enhanced model are illustrated with temporal/spatial maxima of hourly PM 2.5 observations each day from smog monitoring stations located in the Beijing–Tianjin–Hebei geographical region between 2014 and 2019. The proposed model performs more precisely on fittings compared with other previous models dealing with maxima with autoregressive parameter dynamics, and provides relatively accurate prediction as well. The findings enhance the understanding of how severe extreme smog scenarios can be and provide useful information for the central/local government to conduct coordinated PM 2.5 control and treatment. For completeness, probabilistic properties of the proposed model were investigated. Statistical estimation based on the conditional maximum likelihood principle is established. To demonstrate the estimation and inference efficiency of studies, extensive simulations were also implemented.

Alpha Power-Kumaraswamy Distribution with An Application on Survival Times of Cancer Patients

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Fatima Ulubekova ◽  
Gamze Ozel
Keyword(s):  
Hazard Rate ◽  
Real Data ◽  
Rate Function ◽  
Data Sets ◽  
Alpha Power ◽  
Survival Times ◽  
Kumaraswamy Distribution ◽  
Data Application ◽  
The Right ◽  
Better Than

The aim of the study is to obtain the alpha power Kumaraswamy (APK) distribution. Some main statistical properties of the APK distribution are investigated including survival, hazard rate and quantile functions, skewness, kurtosis, order statistics. The hazard rate function of the proposed distribution could be useful to model data sets with bathtub hazard rates. We provide a real data application and show that the APK distribution is better than the other compared distributions fort the right-skewed data sets.

scholarly journals The four-parameter exponentiated Weibull model with Copula, properties and real data modeling.

2021 ◽  
pp. 649-667
Author(s):  
Wahid Shehata ◽  
Haitham M. Yousof
Keyword(s):  
Estimation Method ◽  
Real Data ◽  
Weibull Model ◽  
Hazard Rates ◽  
Survival Times ◽  
New Model ◽  
Clayton Copula ◽  
Failure Times ◽  
Mathematical Properties ◽  
Exponentiated Weibull

A new four-parameter lifetime model is introduced and studied. The new model derives its flexibility and wide applicability from the well-known exponentiated Weibull model. Many bivariate and the multivariate type versions are derived using the Morgenstern family and Clayton copula. The new density can exhibit many important shapes with different skewness and kurtosis which can be unimodal and bimodal. The new hazard rate can be decreasing, J-shape, U-shape, constant, increasing, upside down and increasing-constant hazard rates. Various of its structural mathematical properties are derived. Graphical simulations are used in assessing the performance of the estimation method. We proved empirically the importance and flexibility of the new model in modeling various types of data such as failure times, remission times, survival times and strengths data.

scholarly journals The Two-Parameter Odd Lindley Weibull Lifetime Model with Properties and Applications

2018 ◽  
Vol 7 (4) ◽  
pp. 57 ◽  
Author(s):  
Jehhan. A. Almamy ◽  
Mohamed Ibrahim ◽  
M. S. Eliwa ◽  
Saeed Al-mualim ◽  
Haitham M. Yousof
Keyword(s):  
Maximum Likelihood ◽  
Real Data ◽  
Weibull Model ◽  
Good Alternative ◽  
Model Parameters ◽  
Data Sets ◽  
New Model ◽  
Lifetime Model ◽  
Two Parameter ◽  
Better Than

In this work, we study the two-parameter Odd Lindley Weibull lifetime model. This distribution is motivated by the wide use of the Weibull model in many applied areas and also for the fact that this new generalization provides more flexibility to analyze real data. The Odd Lindley Weibull density function can be written as a linear combination of the exponentiated Weibull densities. We derive explicit expressions for the ordinary and incomplete moments, moments of the (reversed) residual life, generating functions and order statistics. We discuss the maximum likelihood estimation of the model parameters. We assess the performance of the maximum likelihood estimators in terms of biases, variances, mean squared of errors by means of a simulation study. The usefulness of the new model is illustrated by means of two real data sets. The new model provides consistently better fits than other competitive models for these data sets. The Odd Lindley Weibull lifetime model is much better than \ Weibull, exponential Weibull, Kumaraswamy Weibull, beta Weibull, and the three parameters odd lindly Weibull with three parameters models so the Odd Lindley Weibull model is a good alternative to these models in modeling glass fibres data as well as the Odd Lindley Weibull model is much better than the Weibull, Lindley Weibull transmuted complementary Weibull geometric and beta Weibull models so it is a good alternative to these models in modeling time-to-failure data.

scholarly journals A New Flexible Statistical Model: Simulating and Modeling the Survival Times of COVID-19 Patients in China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Xiaofeng Liu ◽  
Zubair Ahmad ◽  
Saima K. Khosa ◽  
M. Yusuf ◽  
Osama Abdulaziz Alamri ◽  
...  
Keyword(s):  
Statistical Model ◽  
Monte Carlo Study ◽  
Weibull Model ◽  
Rate Function ◽  
Model Parameters ◽  
Survival Times ◽  
New Model ◽  
Proposed Model ◽  
Likelihood Approach ◽  
Extended Weibull Distribution

The spread of the COVID-19 epidemic, since December 2019, has caused much damage around the world, disturbed every aspect of daily life, and has become a serious health threat. The COVID-19 epidemic impacted nearly 150 countries around the globe between December 2019 and March 2020. Since December 2019, researchers have been trying to develop new suitable statistical models to adequately describe the behavior of this deadly pandemic. In this paper, a flexible statistical model has been proposed that can be used to model the lifetime events associated with this deadly pandemic. The new distribution is derived from the combination of an extended Weibull distribution and a trigonometric strategy referred to as the arcsine-X approach. Hence, the new model may be referred to as the arcsine new flexible extended Weibull model. The proposed model is capable of capturing five different behaviors of the hazard rate function. The model parameters are estimated via the maximum likelihood approach. Furthermore, a Monte Carlo study is conducted to assess the behavior of the estimators. Finally, the applicability of the new model is demonstrated using the data of fifty-three patients taken from a hospital in China.

scholarly journals Modeling the survival times of the COVID-19 patients with a new statistical model: A case study from China

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254999
Author(s):  
Xiaofeng Liu ◽  
Zubair Ahmad ◽  
Ahmed M. Gemeay ◽  
Alanazi Talal Abdulrahman ◽  
E. H. Hafez ◽  
...  
Keyword(s):  
Weibull Distribution ◽  
Statistical Model ◽  
Medical Science ◽  
Survival Times ◽  
Data Set ◽  
Monte Carlo Simulation Study ◽  
Modified Weibull Distribution ◽  
Related Data ◽  
Proposed Model ◽  
Modified Weibull

Over the past few months, the spread of the current COVID-19 epidemic has caused tremendous damage worldwide, and unstable many countries economically. Detailed scientific analysis of this event is currently underway to come. However, it is very important to have the right facts and figures to take all possible actions that are needed to avoid COVID-19. In the practice and application of big data sciences, it is always of interest to provide the best description of the data under consideration. The recent studies have shown the potential of statistical distributions in modeling data in applied sciences, especially in medical science. In this article, we continue to carry this area of research, and introduce a new statistical model called the arcsine modified Weibull distribution. The proposed model is introduced using the modified Weibull distribution with the arcsine-X approach which is based on the trigonometric strategy. The maximum likelihood estimators of the parameters of the new model are obtained and the performance these estimators are assessed by conducting a Monte Carlo simulation study. Finally, the effectiveness and utility of the arcsine modified Weibull distribution are demonstrated by modeling COVID-19 patients data. The data set represents the survival times of fifty-three patients taken from a hospital in China. The practical application shows that the proposed model out-classed the competitive models and can be chosen as a good candidate distribution for modeling COVID-19, and other related data sets.

scholarly journals A REVIEW OF PROMINENT MODELS OF TEAM ROLES AND CONCEPTUALIZING A NEW MODEL

2020 ◽  
Vol 8 (3) ◽  
pp. 1341-1349
Author(s):  
Divya Nair ◽  
N Meena Rani
Keyword(s):  
Conceptual Model ◽  
Factor Model ◽  
Five Factor Model ◽  
Team Building ◽  
New Model ◽  
Comprehensive List ◽  
Proposed Model ◽  
The Right ◽  
Critical Aspects

Purpose of the study: This study aims to arrive at a new conceptual model of team roles that minimizes the weaknesses and maximizes the strengths of the prominent existing models. This study attempts to connect the new conceptual model of team roles with the five-factor model of personality. Methodology: Prominent existing models of team roles were compared and contrasted amongst themselves. Each model was carefully studied to identify underlying strengths and weaknesses. A comprehensive list of team roles with definitions from each model was put together. The list was carefully examined to identify team roles that can be merged or eliminated. A new model was conceptualized by merging and eliminating team roles wherever necessary. Main Findings: Each of the prominent existing models reviewed missed some critical aspects when contrasted with each other. There is a duplication of roles in some models while some important roles are missing in other models. A more comprehensive conceptual model has been proposed. Applications of this study: The conceptual model proposed in this study can be further tested and developed to create team role inventories. This model can be useful for team building in organizations of all kinds. The model would help in identifying the right members for a new team as well as in predicting outcomes of intact teams. Novelty/Originality of this study: The new conceptual model of team roles proposed in this study connects with the contemporarily relevant five-factor model of personality. This makes it different from previously existing models. The proposed model encompasses the strengths and avoids the weaknesses of past models.  

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