Copula Additive Distributional Regression Using R
Published on 24. June 2025
152 pages
978-1-040-35794-1 (ISBN)
Description
Copula additive distributional regression enables the joint modeling of multiple outcomes, an essential aspect of many real-world research problems. This book provides an accessible overview of this modeling approach, with a particular focus on its implementation in the GJRM R package, developed by the authors. The emphasis is on bivariate responses with empirical illustrations drawn from diverse fields such as health and medicine, epidemiology, economics and social sciences.
Key Features:
Provides a comprehensive overview of joint regression modeling for multiple outcomes, with a focus on bivariate responses
Offers a practical approach with real-world examples from various fields
Demonstrates the implementation of all the discussed models using the GJRM package in R
Includes supplementary resources such as data accessible through the GJRM.data package in R and additional code available on the authors' webpages
This book is designed for graduate students, researchers, practitioners and analysts who are interested in using copula additive distributional regression for the joint modeling of bivariate outcomes. The methodology is accessible to readers with a basic understanding of core statistics and probability, regression, copula modeling and R.
Key Features:
Provides a comprehensive overview of joint regression modeling for multiple outcomes, with a focus on bivariate responses
Offers a practical approach with real-world examples from various fields
Demonstrates the implementation of all the discussed models using the GJRM package in R
Includes supplementary resources such as data accessible through the GJRM.data package in R and additional code available on the authors' webpages
This book is designed for graduate students, researchers, practitioners and analysts who are interested in using copula additive distributional regression for the joint modeling of bivariate outcomes. The methodology is accessible to readers with a basic understanding of core statistics and probability, regression, copula modeling and R.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
5 Tables, black and white; 30 Line drawings, black and white; 30 Illustrations, black and white
File size
7,42 MB
ISBN-13
978-1-040-35794-1 (9781040357941)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Giampiero Marra | Rosalba Radice
Copula Additive Distributional Regression Using R
Book
06/2025
1st Edition
Chapman & Hall/CRC
€109.30
Shipment within 10-20 days
Giampiero Marra
Copula Additive Distributional Regression Using R
Book
06/2025
CRC Press
Unfortunately, price unknown
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Persons
Giampiero Marra is a Professor of Statistics in the Department of Statistical Science at University College London (UCL). He holds a degree in Statistics and Economics from the University of Bologna (2004) and began his career in consultancy roles in the private sector. In 2007, he completed an MSc in Statistics at UCL and successfully defended his PhD thesis at the University of Bath in November 2010. Giampiero joined UCL as a faculty member in September 2010.
Rosalba Radice is a Professor of Statistics at Bayes Business School, City St George's, University of London. After earning her PhD in Statistics from the University of Bath, she held positions as a research assistant and research fellow at the London School of Hygiene and Tropical Medicine. From 2012 to 2018, Rosalba served as Lecturer, Senior Lecturer and then Reader in Statistics at Birkbeck, University of London.
For over 15 years, Giampiero and Rosalba have collaborated extensively to advance methodological, computational and applied statistics. Their research spans diverse areas, including penalized likelihood-based inference, copula regression and survival analysis, with impactful applications in fields such as healthcare, economics, epidemiology and the social sciences. As part of their work, they developed the GJRM package for R, which enables researchers and practitioners to implement these methods effectively while promoting transparency and reproducibility.
Rosalba Radice is a Professor of Statistics at Bayes Business School, City St George's, University of London. After earning her PhD in Statistics from the University of Bath, she held positions as a research assistant and research fellow at the London School of Hygiene and Tropical Medicine. From 2012 to 2018, Rosalba served as Lecturer, Senior Lecturer and then Reader in Statistics at Birkbeck, University of London.
For over 15 years, Giampiero and Rosalba have collaborated extensively to advance methodological, computational and applied statistics. Their research spans diverse areas, including penalized likelihood-based inference, copula regression and survival analysis, with impactful applications in fields such as healthcare, economics, epidemiology and the social sciences. As part of their work, they developed the GJRM package for R, which enables researchers and practitioners to implement these methods effectively while promoting transparency and reproducibility.
Content
1. Core concepts in copula regression. 2. Continuous outcomes. 3. Count outcomes . 4. Survival outcomes. 5. Binary outcomes . 6. Ordinal outcomes. 7. Binary outcome with partial observability. 8. Ordinal and continuous outcomes. 9. Binary and continuous outcomes. 10. Binary and count outcomes. 11. Count and continuous outcomes. 12. Binary outcome with binary treatment effect. 13. Time-to-event outcome with binary treatment effect. 14. Binary outcome with missingness not at random.
