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Statistical Modelling by Exponential Families

Statistical Modelling by Exponential Families

£29.99

Part of Institute of Mathematical Statistics Textbooks

  • Publication planned for: July 2019
  • availability: Not yet published - available from July 2019
  • format: Paperback
  • isbn: 9781108701112

£ 29.99
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  • 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.

    • Expands and extends the theory and application of exponential families within one concise volume
    • Uses recurrent themes in examples and exercises to build familiarity with the models
    • Gives a concise account of the philosophy of Per Martin-Löf, connecting statistical modelling with ideas in statistical physics
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    Product details

    • Publication planned for: July 2019
    • format: Paperback
    • isbn: 9781108701112
    • dimensions: 228 x 152 mm
    • contains: 45 b/w illus. 90 exercises
    • availability: Not yet published - available from July 2019
  • Table of Contents

    Preface
    1. Random walks on graphs
    2. Uniform spanning tree
    3. Percolation and self-avoiding walk
    4. Association and influence
    5. Further percolation
    6. Contact process
    7. Gibbs states
    8. Random-cluster model
    9. Quantum Ising model
    10. Interacting particle systems
    11. Random graphs
    12. Lorentz gas
    References
    Index.

  • Author

    Rolf Sundberg, Stockholms Universitet
    Rolf Sundberg is Professor Emeritus of Statistical Science at Stockholms Universitet. His work embraces both theoretical and applied statistics, including principles of statistics, exponential families, regression, chemometrics, stereology, survey sampling inference, molecular biology, and paleoclimatology. In 2003, he won the award for best theoretical paper in the Journal of Chemometrics for his work on multivariate calibration, and in 2017 he was named Statistician of the Year by the Swedish Statistical Association.

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