Copula Additive Distributional Regression Using R
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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 bivar...
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' 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 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' 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.
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