Unified treatment of life distributions /
Wafaa Yahia Ahmed
Unified treatment of life distributions / معالجه موحده لبعض توزيعات الحياه Wafaa Yahia Ahmed ; Supervised Abdelhadi Nabih Ahmed , Hiba Zeyada Muhammed - Cairo : Wafaa Yahia Ahmed , 2020 - 134 Leaves : charts , facsimiles ; 30cm
Thesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Mathematical Statistics
Statistical distributions are used to model real life phenomena. In many applied sciences such as medicine, engineering and finance, amongst others, modeling and analyzing lifetime data are crucial. Several lifetime distributions have been used to model such data.The quality of the procedures used in a statistical analysis depends heavily on the assumed probability model. Seeking flexibility of modeling different types of phenomena remains a strong reason for developing new distributions. Since there is a clear need for extended forms of these distributions, a significant progress has been made towards the generalization of some well-known distributions and their successful applications in different problems. Although, the previous efforts have resulted in more flexible distributions, still remains many important problems where the real data does not follow any of the classical or the extended probability models.The main aim of this thesis is to introduce a new generator.The new generator, based on the star-shaped property, grantees the existences of some well know properties for the generated classes and distributions for any non-negative random variables. The new class is named the composed -GQ class.To examine the performance of the new generator and the generated models in fitting several data, a new produced model called composed- inverted generalized exponential- exponential is derived and compared with some well-known models to fit different types of data. This comparison has shown that the introduced model based on the newly suggested generator has resulted in the best fit to all sets of data
Average Interval Lengths (AIL) Life distributions Statistical distributions
Unified treatment of life distributions / معالجه موحده لبعض توزيعات الحياه Wafaa Yahia Ahmed ; Supervised Abdelhadi Nabih Ahmed , Hiba Zeyada Muhammed - Cairo : Wafaa Yahia Ahmed , 2020 - 134 Leaves : charts , facsimiles ; 30cm
Thesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Mathematical Statistics
Statistical distributions are used to model real life phenomena. In many applied sciences such as medicine, engineering and finance, amongst others, modeling and analyzing lifetime data are crucial. Several lifetime distributions have been used to model such data.The quality of the procedures used in a statistical analysis depends heavily on the assumed probability model. Seeking flexibility of modeling different types of phenomena remains a strong reason for developing new distributions. Since there is a clear need for extended forms of these distributions, a significant progress has been made towards the generalization of some well-known distributions and their successful applications in different problems. Although, the previous efforts have resulted in more flexible distributions, still remains many important problems where the real data does not follow any of the classical or the extended probability models.The main aim of this thesis is to introduce a new generator.The new generator, based on the star-shaped property, grantees the existences of some well know properties for the generated classes and distributions for any non-negative random variables. The new class is named the composed -GQ class.To examine the performance of the new generator and the generated models in fitting several data, a new produced model called composed- inverted generalized exponential- exponential is derived and compared with some well-known models to fit different types of data. This comparison has shown that the introduced model based on the newly suggested generator has resulted in the best fit to all sets of data
Average Interval Lengths (AIL) Life distributions Statistical distributions