Statistical Modeling and Computation

Authors: Kroese, Dirk P., C.C. Chan, Joshua

  • An integrated treatment of statistical inference and computation helps the reader gain a firm understanding of both theory and practice
  • Discusses modern computation techniques including Markov chain Monte Carlo methods and the Expectation Maximization algorithm
  • Includes numerous solved examples and exercises
  • Includes computer codes and a brief programming primer in MATLAB for students 
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eBook $59.99
price for USA (gross)
  • ISBN 978-1-4614-8775-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
price for USA
  • ISBN 978-1-4614-8774-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $79.99
price for USA
  • ISBN 978-1-4939-5332-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
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About this Textbook

This textbook on statistical modeling and statistical inference will assist advanced undergraduate and graduate students. Statistical Modeling and Computation provides a unique introduction to modern Statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of Mathematical Statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. Each of the three parts will cover topics essential to university courses. Part I covers the fundamentals of probability theory. In Part II, the authors introduce a wide variety of classical models that include, among others, linear regression and ANOVA models. In Part III, the authors address the statistical analysis and computation of various advanced models, such as generalized linear, state-space and Gaussian models. Particular attention is paid to fast Monte Carlo techniques for Bayesian inference on these models. Throughout the book the authors include a large number of illustrative examples and solved problems. The book also features a section with solutions, an appendix that serves as a MATLAB primer, and a mathematical supplement.​

About the authors

Dirk P. Kroese is a Professor of Mathematics and Statistics at The University of Queensland. He is fascinated by anything that deals with the theory and application of randomness. He has written over 90 publications in a wide range of areas in probability and statistics,  including three influential books: The Cross-Entropy Method and Simulation and the Monte Carlo Method, Second Edition, both with Reuven Rubinstein, and Handbook of Monte Carlo Methods, with Thomas Taimre and Zdravko Botev.

Joshua Chan is a Senior Lecturer at the Research School of Economics, Australian National University. His current research focuses on detecting and modeling time-varying structures in macroeconomic data using simulation-based methods. He has published widely in leading international journals such as Journal of Econometrics, Journal of Business and Economic Statistics, and Journal of Computational and Graphical Statistics.

Reviews

“Fundamentals of probability and modeling are presented in a rigorous language and the transition to more advanced chapters is almost smooth. Explanations are precise, both verbally and mathematically. Throughout the book, cross-references are made so that the reader can find further or related topics in other parts of the book. Readers interested in mathematical rigor will find this book rewarding. …

Another strength of the book lies in the wealth and variety of exercises at the end of each chapter. The exercises (some with complete solutions) range from mathematical proofs and model building to programming. Solutions for select problems are presented at the end of the book. …

[This] book is outstanding in terms of coverage of topics, rigorous language and integration of computation.” (Abdolvahab Khademi, Journal of Statistical Software, August 2015)        

Table of contents (13 chapters)

  • Probability Models

    Kroese, Dirk P. (et al.)

    Pages 3-21

  • Random Variables and Probability Distributions

    Kroese, Dirk P. (et al.)

    Pages 23-61

  • Joint Distributions

    Kroese, Dirk P. (et al.)

    Pages 63-97

  • Common Statistical Models

    Kroese, Dirk P. (et al.)

    Pages 101-120

  • Statistical Inference

    Kroese, Dirk P. (et al.)

    Pages 121-159

Buy this book

eBook $59.99
price for USA (gross)
  • ISBN 978-1-4614-8775-3
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
price for USA
  • ISBN 978-1-4614-8774-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $79.99
price for USA
  • ISBN 978-1-4939-5332-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Statistical Modeling and Computation
Authors
Copyright
2014
Publisher
Springer-Verlag New York
Copyright Holder
The Author(s)
Distribution Rights
Distribution rights for India: Researchco Book Centre, New Delhi, India
eBook ISBN
978-1-4614-8775-3
DOI
10.1007/978-1-4614-8775-3
Hardcover ISBN
978-1-4614-8774-6
Softcover ISBN
978-1-4939-5332-5
Edition Number
1
Number of Pages
XX, 400
Number of Illustrations and Tables
106 b/w illustrations, 8 illustrations in colour
Topics