Copula Additive Distributional Regression Using R

Giampiero Marra, Rosalba Radice

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English

Chapman & Hall/CRC
24 June 2025

Epidemiology & medical statistics; Probability & statistics; Programming & scripting languages: general

Series: Chapman & Hall/CRC The R Series

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.

By: Giampiero Marra, Rosalba Radice
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 254mm, Width: 178mm,
ISBN: 9781032973111
ISBN 10: 1032973110
Series: Chapman & Hall/CRC The R Series
Pages: 136
Publication Date: 24 June 2025
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Forthcoming

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.