Bayesian Analysis of Probability Distributions

Kawsar Fatima

ISBN 10: 9286673051 / ISBN 13: 9789286673054

Published by Independent Author, 2023

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - '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.

Seller Inventory # 9789286673054

Bibliographic Details

• Title: Bayesian Analysis of Probability Distributions
• Publisher: Independent Author
• Publication Date: 2023
• Language: English
• ISBN 10: 9286673051
• ISBN 13: 9789286673054
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 229W x 152H x 9D millimeters 229 millimeters width by 152 millimeters height by 9 millimeters depth
• Weight: 223 grams

About this title

Synopsis

"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.