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Titlebook: Monte-Carlo Simulation-Based Statistical Modeling; Ding-Geng‘(Din) Chen,John Dean Chen Book 2017 The Editor(s) (if applicable) and The Aut

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發(fā)表于 2025-3-21 17:06:44 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Monte-Carlo Simulation-Based Statistical Modeling
編輯Ding-Geng‘(Din) Chen,John Dean Chen
視頻videohttp://file.papertrans.cn/640/639139/639139.mp4
概述Written by experts actively engaged in Monte-Carlo simulation-based statistical modeling.Includes timely discussions and presentations on methodological developments and concrete applications.Introduc
叢書名稱ICSA Book Series in Statistics
圖書封面Titlebook: Monte-Carlo Simulation-Based Statistical Modeling;  Ding-Geng‘(Din) Chen,John Dean Chen Book 2017 The Editor(s) (if applicable) and The Aut
描述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.
出版日期Book 2017
關鍵詞Monte-Carlo Techniques; Statistical Modelling; Importance Sampling; Multiple Integration; Simulation; Eff
版次1
doihttps://doi.org/10.1007/978-981-10-3307-0
isbn_softcover978-981-10-9839-0
isbn_ebook978-981-10-3307-0Series ISSN 2199-0980 Series E-ISSN 2199-0999
issn_series 2199-0980
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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沙發(fā)
發(fā)表于 2025-3-21 20:17:34 | 只看該作者
https://doi.org/10.1007/978-981-10-3307-0Monte-Carlo Techniques; Statistical Modelling; Importance Sampling; Multiple Integration; Simulation; Eff
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發(fā)表于 2025-3-22 03:14:38 | 只看該作者
978-981-10-9839-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
地板
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發(fā)表于 2025-3-22 09:30:38 | 只看該作者
Ding-Geng‘(Din) Chen,John Dean ChenWritten by experts actively engaged in Monte-Carlo simulation-based statistical modeling.Includes timely discussions and presentations on methodological developments and concrete applications.Introduc
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發(fā)表于 2025-3-22 16:16:24 | 只看該作者
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Book 2017s 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 mode
8#
發(fā)表于 2025-3-22 21:39:21 | 只看該作者
Book 2017odel 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.
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