Monte-Carlo Simulation-Based Statistical Modeling

Monte-Carlo Simulation-Based Statistical Modeling

Ding-Geng (Din) Chen, John Dean Chen (eds.)
How much do you like this book?
What’s the quality of the file?
Download the book for quality assessment
What’s the quality of the downloaded files?

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.

Year:
2017
Edition:
1
Publisher:
Springer Singapore
Language:
english
Pages:
438
ISBN 10:
9811033072
ISBN 13:
9789811033070
Series:
ICSA Book Series in Statistics
File:
PDF, 10.02 MB
IPFS:
CID , CID Blake2b
english, 2017
Read Online
Conversion to is in progress
Conversion to is failed

Most frequently terms