G Families of Probability Distributions
  1. 358 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

About this book

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.

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Information

Publisher
CRC Press
Year
2023
Print ISBN
9781032140650
eBook ISBN
9781000860412

Table of contents

  1. Cover
  2. Title
  3. Copyright
  4. Preface
  5. Acknowledgement
  6. Contents
  7. 1. A New Compound G Family of Distributions: Properties, Copulas, Characterizations, Real Data Applications with Different Methods of Estimation
  8. 2. A Novel Family of Continuous Distributions: Properties, Characterizations, Statistical Modeling and Different Estimation Methods
  9. 3. On the use of Copulas to Construct Univariate Generalized Families of Continuous Distributions
  10. 4. A Family of Continuous Probability Distributions: Theory, Characterizations, Properties and Different Copulas
  11. 5. New Odd Log-Logistic Family of Distributions: Properties, Regression Models and Applications
  12. 6. On the Family of Generalized Topp-Leone Arcsin Distributions
  13. 7. The Truncated Modified Lindley Generated Family of Distributions
  14. 8. An Extension of the Weibull Distribution via Alpha Logarithmic G Family with Associated Quantile Regression Modeling and Applications
  15. 9. The Topp-Leone-G Power Series Distribution: Its Properties and Applications
  16. 10. Exponentiated Generalized General Class of Inverted Distributions: Estimation and Prediction
  17. 11. A New Class of Discrete Distribution Arising as an Analogue of Gamma-Lomax Distribution: Properties and Applications
  18. 12. New Compounding Lifetime Distributions with Application to Hard Drive Reliability
  19. 13. Comparing the Performance of G-family Probability Distribution for Modeling Rainfall Data
  20. 14. Record-Based Transmuted Kumaraswamy Generalized Family of Distributions: Properties and Application
  21. 15. Finding an Efficient Distribution to Analyze Lifetime Data through Simulation Study
  22. 16. Exponentiated Muth Distribution: Properties and Applications
  23. 17. Exponentiated Discrete Modified Lindley Distribution and its Applications in the Healthcare Sector
  24. 18. Length Biased Weighted New Quasi Lindley Distribution: Statistical Properties and Applications
  25. 19. A New Alpha Power Transformed Weibull Distribution: Properties and Applications
  26. 20. An Extension of Topp-Leone Distribution with Increasing, Decreasing and Bathtub Hazard Functions
  27. 21. Testing the Goodness of Fit in Instrumental Variables Models
  28. 22. Probability Distribution Analysis for Rainfall Scenarios—A Case Study
  29. Index

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Yes, you can access G Families of Probability Distributions by Mir Masoom Ali, Irfan Ali, Haitham M. Yousof, Mohamed Ibrahim Mohamed Ahmed, Mir Masoom Ali,Irfan Ali,Haitham M. Yousof,Mohamed Ibrahim Mohamed Ahmed in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over 1.5 million books available in our catalogue for you to explore.