Editors:
- 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
- Includes supplementary material: sn.pub/extras
Part of the book series: ICSA Book Series in Statistics (ICSABSS)
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Table of contents (19 chapters)
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Back Matter
About this book
Editors and Affiliations
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Gillings School of Global Public Health, University of North Carolina, Chapel Hill, USA
Ding-Geng (Din) Chen
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Risk Management, Credit Suisse Risk Management, New York, USA
John Dean Chen
About the editors
Bibliographic Information
Book Title: Monte-Carlo Simulation-Based Statistical Modeling
Editors: Ding-Geng (Din) Chen, John Dean Chen
Series Title: ICSA Book Series in Statistics
DOI: https://doi.org/10.1007/978-981-10-3307-0
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2017
Hardcover ISBN: 978-981-10-3306-3Published: 10 February 2017
Softcover ISBN: 978-981-10-9839-0Published: 14 July 2018
eBook ISBN: 978-981-10-3307-0Published: 01 February 2017
Series ISSN: 2199-0980
Series E-ISSN: 2199-0999
Edition Number: 1
Number of Pages: XX, 430
Number of Illustrations: 31 b/w illustrations, 33 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Biostatistics
Industry Sectors: Biotechnology, IT & Software, Pharma