Statistical Modelling by Exponential Families
eBook - PDF

Statistical Modelling by Exponential Families

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Statistical Modelling by Exponential Families

About this book

This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful distributions in statistical theory, including the normal, gamma, binomial, Poisson, and negative binomial. Strongly motivated by applications, it presents the essential theory and then demonstrates the theory's practical potential by connecting it with developments in areas like item response analysis, social network models, conditional independence and latent variable structures, and point process models. Extensions to incomplete data models and generalized linear models are also included. In addition, the author gives a concise account of the philosophy of Per Martin-Löf in order to connect statistical modelling with ideas in statistical physics, including Boltzmann's law. Written for graduate students and researchers with a background in basic statistical inference, the book includes a vast set of examples demonstrating models for applications and exercises embedded within the text as well as at the ends of chapters.

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Yes, you can access Statistical Modelling by Exponential Families by Rolf Sundberg in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title
  3. Series information
  4. Title page
  5. Copyright information
  6. Dedication
  7. Contents
  8. Examples
  9. Preface
  10. 1 What Is an Exponential Family?
  11. 2 Examples of Exponential Families
  12. 3 Regularity Conditions and Basic Properties
  13. 4 Asymptotic Properties of the MLE
  14. 5 Testing Model-Reducing Hypotheses
  15. 6 Boltzmann’s Law in Statistics
  16. 7 Curved Exponential Families
  17. 8 Extension to Incomplete Data
  18. 9 Generalized Linear Models
  19. 10 Graphical Models for Conditional Independence Structures
  20. 11 Exponential Family Models for Graphs of Social Networks
  21. 12 Rasch Models for Item Response and Related Model Types
  22. 13 Models for Processes in Space or Time
  23. 14 More Modelling Exercises
  24. Appendix A Statistical Concepts and Principles
  25. Appendix B Useful Mathematics
  26. Bibliography
  27. Index