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G Families of Probability Distributions: Theory and Practices [Kietas viršelis]

Edited by (Damietta University, Egypt), Edited by , Edited by (Aligarh Muslim University, India), Edited by (Benha University, Egypt)
  • Formatas: Hardback, 358 pages, aukštis x plotis: 254x178 mm, weight: 834 g, 94 Line drawings, black and white; 7 Halftones, black and white; 101 Illustrations, black and white
  • Išleidimo metai: 31-Mar-2023
  • Leidėjas: CRC Press
  • ISBN-10: 1032140658
  • ISBN-13: 9781032140650
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 358 pages, aukštis x plotis: 254x178 mm, weight: 834 g, 94 Line drawings, black and white; 7 Halftones, black and white; 101 Illustrations, black and white
  • Išleidimo metai: 31-Mar-2023
  • Leidėjas: CRC Press
  • ISBN-10: 1032140658
  • ISBN-13: 9781032140650
Kitos knygos pagal šią temą:
"Statistical distributions are important tools to model the characteristics of data sets observed in different applied sciences such as engineering, medicine, and finance, among others. In the last decade researchers focused on the more complex and flexible distributions, referred to as Generalized or simply G families of continuous distributions to increase the modeling ability of these distributions by adding one or more shape parameters. This book will help future and current researchers in the field of G families of probability distributions"--

Statistical distributions are important tools to model the characteristics of data sets observed in different applied sciences such as engineering, medicine, and finance, among others. This book will help future and current researchers in the field of G families of probability distributions.



Statistical distributions are essential tools to model the characteristics of datasets, such as right or left skewness, bi-modality or multi-modality observed in different applied sciences, such as engineering, medicine, and finance. The well-known distributions like normal, Weibull, gamma and Lindley are extensively used because of their simple forms and identifiability properties. In the last decade, researchers have focused on the more complex and flexible distributions, referred to as Generalized or simply G families of probability distributions, to increase the modelling capability of these distributions by adding one or more shape parameters.

The main aim of this edited book is to present new contributions by researchers in the field of G families of probability distributions. The book will help researchers to:

  • Develop new univariate continuous and discrete G families of probability distributions.
  • Develop new bivariate continuous and discrete G families of probability distributions.
  • Derive beneficial mathematical properties such as ordinary and incomplete moments, moment generating functions, residual life and reversed residual life functions, order statistics, quantile spread ordering and entropies, and some bivariate and multivariate extensions of the new and existing models using a simple-type copula.
Preface iii
Acknowledgement iv
1 A New Compound G Family of Distributions: Properties, Copulas, Characterizations, Real Data Applications with Different Methods of Estimation
1(30)
M. Masoom Ali
Nadeem Shafique Butt
G.G. Hamedani
Saralees Nadarajah
Haitham M. Yousof
Mohamed Ibrahim
2 A Novel Family of Continuous Distributions: Properties, Characterizations, Statistical Modeling and Different Estimation Methods
31(24)
Haitham M. Yousof
M. Masoom Ali
Gauss M. Cordeiro
G.G. Hamedani
Mohamed Ibrahim
3 On the use of Copulas to Construct Univariate Generalized Families of Continuous Distributions
55(10)
Christophe Chesneau
Haitham M. Yousof
4 A Family of Continuous Probability Distributions: Theory, Characterizations, Properties and Different Copulas
65(15)
Mohammad Mehdi Saber
G.G. Hamedani
Haitham M. Yousof
Nadeem Shafique Butt
Basma Ahmed
Mohamed Ibrahim
5 New Odd Log-Logistic Family of Distributions: Properties, Regression Models and Applications
80(14)
Emrah Altun
Morad Alizadeh
Gamze Ozel
Haitham M. Yousof
6 On the Family of Generalized Topp-Leone Arcsin Distributions
94(17)
Vikas Kumar Sharma
Komal Shekhawat
Sanjay Kumar Singh
7 The Truncated Modified Lindley Generated Family of Distributions
111(10)
Lishamol Tomy
Christophe Chesneau
Jiju Gillariose
8 An Extension of the Wei bull Distribution via Alpha Logarithmic G Family with Associated Quantile Regression Modeling and Applications
121(11)
Yunus Akdogan
Kadir Karakaya
Mustafa C. Korkmaz
Fatih Sahin
Asir Gene
9 The Topp-Leone-G Power Series Distribution: Its Properties and Applications
132(12)
Laba Handique
Subrata Chakraborty
M. Masoom Ali
10 Exponentiated Generalized General Class of Inverted Distributions: Estimation and Prediction
144(37)
Abeer A. El-Helbawy Gannat R. Al-Dayian
Asmaa M. Abd Al-Fattah
Rabab E. Abd El-Kader
11 A New Class of Discrete Distribution Arising as an Analogue of Gamma-Lomax Distribution: Properties and Applications
181(15)
Indranil Ghosh
Ayman Alzaatreh
G.G. Hamedani
12 New Compounding Lifetime Distributions with Application to Hard Drive Reliability
196(23)
A. Asgharzadeh
Hassan S. Bakouch
L. Esmaeili
S. Nadarqjah
13 Comparing the Performance of G-family Probability Distribution for Modeling Rainfall Data
219(14)
Md Mostqfizur Rahman
Md Abdul Khalekm A. M. Sayedur Rahman
14 Record-Based Transmuted Kumaraswamy Generalized Family of Distributions: Properties and Application
233(11)
Qazi J. Azhad
Mohd Arshad
Bhagwati Devi
Nancy Khandelwal
Irfan Ali
15 Finding an Efficient Distribution to Analyze Lifetime Data through Simulation Study
244(13)
Anamul Haque Sajib
Trishna Saha
M. Sayedur Rahman
16 Exponentiated Muth Distribution: Properties and Applications
257(22)
R. Maya
Mr. Irshad
Anuresha Krishna
17 Exponentiated Discrete Modified Lindley Distribution and its Applications in the Healthcare Sector
279(9)
Lishamol Tomy
G. Veena
Christophe Chesneau
18 Length Biased Weighted New Quasi Lindley Distribution: Statistical Properties and Applications
288(14)
Aafaq A. Rather
19 A New Alpha Power Transformed Weibull Distribution: Properties and Applications
302(14)
Ashok Kumar Pathak
Mohd Arshad
Sanjeev Bakshi
Mukti Khetan
Sherry Mangla
20 An Extension of Topp-Leone Distribution with Increasing, Decreasing and Bathtub Hazard Functions
316(14)
Unnati Nigam
Arun Kaushik
21 Testing the Goodness of Fit in Instrumental Variables Models
330(14)
Shalabh
Subhra Sankar Dhar
22 Probability Distribution Analysis for Rainfall Scenarios---A Case Study
344(13)
Md Abdul Khalek
Md Mostqfizur Rahaman
Md Kamruzzaman
Md Mesbahul Alam
M. Sayedur Rahman
Index 357
Dr. Mir Masoom Ali is George and Frances Ball Distinguished Professor Emeritus of Statistics at Ball State University in the USA. His current research interest is in the area of G Families of probability distributions and he has published numerous papers in this area.

Dr. Irfan Ali is an Assistant Professor of Statistics at the Department of Statistics and Operations Research, Aligarh Muslim University, India. His current research areas are applied statistics and mathematical programming and he has published more than 100 research papers in these areas.

Dr. Haitham M. Yousof is an Assistant professor of Statistics at the Department of Statistics, Mathematics and Insurance, Benha University, Egypt. His current research areas are probability theory and G Families of probability distributions and he has published more than 200 research papers in these areas.

Dr. Mohamed Ibrahim is an Assistant professor of Statistics at the Department of Applied, Mathematical and Actuarial Statistics, Damietta University, Egypt. His current research areas are probability theory and G Families of probability distributions and he has published several research papers in these areas.