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Bayesian Analysis of Probability Distributions - Kawsar Fatima - Bog

Bag om Bayesian Analysis of Probability Distributions

"Bayesian Analysis of Probability Distributions" by Kawsar Fatima is an essential reference guide for statisticians, data analysts, and researchers. The book provides a comprehensive overview of Bayesian analysis methods for probability distributions, including advanced modeling techniques and the latest developments in computational algorithms. It covers a range of topics, from basic concepts and principles of Bayesian inference to advanced Bayesian hierarchical modeling and model selection. The book provides numerous examples and case studies to illustrate the use of Bayesian analysis in practical applications. It covers a wide range of probability distributions, including univariate, multivariate, continuous, and discrete distributions. The author also discusses the use of Bayesian analysis in fields such as finance, engineering, medicine, and social sciences. Overall, "Bayesian Analysis of Probability Distributions" is an excellent resource for anyone looking to learn or expand their knowledge of Bayesian analysis. With its comprehensive coverage of probability distributions and advanced modeling techniques, this book is an indispensable tool for researchers and practitioners in many fields.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789286673054
  • Indbinding:
  • Paperback
  • Sideantal:
  • 146
  • Udgivet:
  • 10. marts 2023
  • Størrelse:
  • 152x9x229 mm.
  • Vægt:
  • 223 g.
  • 8-11 hverdage.
  • 6. december 2024
På lager

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Beskrivelse af Bayesian Analysis of Probability Distributions

"Bayesian Analysis of Probability Distributions" by Kawsar Fatima is an essential reference guide for statisticians, data analysts, and researchers. The book provides a comprehensive overview of Bayesian analysis methods for probability distributions, including advanced modeling techniques and the latest developments in computational algorithms. It covers a range of topics, from basic concepts and principles of Bayesian inference to advanced Bayesian hierarchical modeling and model selection.
The book provides numerous examples and case studies to illustrate the use of Bayesian analysis in practical applications. It covers a wide range of probability distributions, including univariate, multivariate, continuous, and discrete distributions. The author also discusses the use of Bayesian analysis in fields such as finance, engineering, medicine, and social sciences.
Overall, "Bayesian Analysis of Probability Distributions" is an excellent resource for anyone looking to learn or expand their knowledge of Bayesian analysis. With its comprehensive coverage of probability distributions and advanced modeling techniques, this book is an indispensable tool for researchers and practitioners in many fields.

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