Copula Additive Distributional Regression Using R (Chapman & Hall/CRC The R Series)

Copula Additive Distributional Regression Using R (Chapman & Hall/CRC The R Series)

Copula Additive Distributional Regression Using R (Chapman & Hall/CRC The R Series)

by: Giampiero Marra (Author), Rosalba Radice (Author)

Edition: 1st

Publication Date: 2025-06-24

Language: English

Print Length: 152 pages

ISBN-10: 1032973110

ISBN-13: 9781032973111

Book 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 responsesOffers a practical approach with real-world examples from various fieldsDemonstrates the implementation of all the discussed models using the GJRM package in RIncludes supplementary resources such as data accessible through the GJRM.data package in R and additional code available on the authors’ webpagesThis 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.

Editorial Reviews

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 responsesOffers a practical approach with real-world examples from various fieldsDemonstrates the implementation of all the discussed models using the GJRM package in RIncludes supplementary resources such as data accessible through the GJRM.data package in R and additional code available on the authors’ webpagesThis 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.

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