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ICSA Book Series in Statistics

Monte-Carlo Simulation-Based Statistical Modeling

Editors: Chen, Ding-Geng, Chen, John Dean (Eds.)

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  • Written by experts actively engaged in Monte-Carlo simulation-based statistical modeling 
  • Includes timely discussions and presentations on methodological developments and concrete applications
  • Introduces data and computer programs that will be made publicly available, allowing readers to replicate the model developments
  • Features readily adoptable and extendable, high-impact methods
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eBook 91,62 €
price for Spain (gross)
  • ISBN 978-981-10-3307-0
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 114,39 €
price for Spain (gross)
  • ISBN 978-981-10-3306-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 114,39 €
price for Spain (gross)
  • ISBN 978-981-10-9839-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.

About the authors

Professor Ding-Geng Chen is a fellow of the American Statistical Association and currently the Wallace Kuralt distinguished professor at the University of North Carolina at Chapel Hill. He was a professor at the University of Rochester and the Karl E. Peace endowed eminent scholar chair in biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceuticals and government agencies with extensive expertise in clinical trial biostatistics and public health statistics. Professor Chen has written more than 150 referred professional publications and co-authored and co-edited eight books on clinical trial methodology, meta-analysis, causal-inference and public health statistics. 

Mr. John Dean Chen is specialized in Monte-Carlo simulations in modelling financial market risk. In his career on Wall Street, he worked in Market Risk in commodities trading, structuring notes on the Exotics Interest Rate Derivatives desk at Barclays Capital. During his career in the financial industry, he witnessed in person the unfolding of the financial crisis, and the immediate aftermath consuming much of the financial industry. In its wake, a dizzying array of regulations were made from the government, severely limiting the businesses that once made banks so profitable. Mr Chen transitioned back to the Risk side of the business working in Market and Model Risk. He is currently a Vice President at Credit Suisse specializing in regulatory stress testing with  Monte-Carlo simulations. He graduated from the University of Washington with a dual Bachelors of Science in Applied Mathematics and Economics.  

Table of contents (19 chapters)

Table of contents (19 chapters)
  • Joint Generation of Binary, Ordinal, Count, and Normal Data with Specified Marginal and Association Structures in Monte-Carlo Simulations

    Pages 3-15

    Demirtas, Hakan (et al.)

  • Improving the Efficiency of the Monte-Carlo Methods Using Ranked Simulated Approach

    Pages 17-40

    Samawi, Hani Michel

  • Normal and Non-normal Data Simulations for the Evaluation of Two-Sample Location Tests

    Pages 41-57

    Hoag, Jessica R. (et al.)

  • Anatomy of Correlational Magnitude Transformations in Latency and Discretization Contexts in Monte-Carlo Studies

    Pages 59-84

    Demirtas, Hakan (et al.)

  • Monte-Carlo Simulation of Correlated Binary Responses

    Pages 85-105

    Lalonde, Trent L.

Buy this book

eBook 91,62 €
price for Spain (gross)
  • ISBN 978-981-10-3307-0
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 114,39 €
price for Spain (gross)
  • ISBN 978-981-10-3306-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 114,39 €
price for Spain (gross)
  • ISBN 978-981-10-9839-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Monte-Carlo Simulation-Based Statistical Modeling
Editors
  • Ding-Geng Chen
  • John Dean Chen
Series Title
ICSA Book Series in Statistics
Copyright
2017
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-10-3307-0
DOI
10.1007/978-981-10-3307-0
Hardcover ISBN
978-981-10-3306-3
Softcover ISBN
978-981-10-9839-0
Series ISSN
2199-0980
Edition Number
1
Number of Pages
XX, 430
Number of Illustrations
31 b/w illustrations, 33 illustrations in colour
Topics