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Monte-Carlo Simulation-Based Statistical Modeling

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Monte-Carlo Simulation-Based Statistical Modeling Synopsis

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 This Edition

ISBN: 9789811098390
Publication date:
Author: DingGeng Din Chen, John Dean Chen
Publisher: Springer an imprint of Springer Nature Singapore
Format: Paperback
Pagination: 430 pages
Series: ICSA Book Series in Statistics
Genres: Probability and statistics

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