Monte-Carlo Simulation-Based Statistical Modeling

Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Science & Nature, Mathematics, Science, Biological Sciences
Cover of the book Monte-Carlo Simulation-Based Statistical Modeling by , Springer Singapore
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9789811033070
Publisher: Springer Singapore Publication: February 1, 2017
Imprint: Springer Language: English
Author:
ISBN: 9789811033070
Publisher: Springer Singapore
Publication: February 1, 2017
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer Singapore

Cover of the book The Transition from Graduation to Work by
Cover of the book Atlas of Environmental Risks Facing China Under Climate Change by
Cover of the book Subdivision Surface Modeling Technology by
Cover of the book Data Science by
Cover of the book Biomaterials for Musculoskeletal Regeneration by
Cover of the book Energy Conservation for IoT Devices by
Cover of the book Severance Payment and Labor Mobility by
Cover of the book Data Science and Analytics by
Cover of the book CEO School by
Cover of the book Local Government in Australia by
Cover of the book Understanding the Impact of INSET on Teacher Change in China by
Cover of the book Phytoplasmas: Plant Pathogenic Bacteria - I by
Cover of the book Designing Embedded Systems with Arduino by
Cover of the book Locomotives and Rail Road Transportation by
Cover of the book Chinese and Indian Medicine Today by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy