Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, With Applications (Cambridge in Statistical and Probabilistic Mathematics, 56) - Hardcover

Buch 44 von 46: Cambridge Series in Statistical and Probabilistic Mathematics

Stasinopoulos, Mikis D.; Kneib, Thomas; Klein, Nadja; Mayr, Andreas; Heller, Gillian Z.

 
9781009410069: Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, With Applications (Cambridge in Statistical and Probabilistic Mathematics, 56)

Inhaltsangabe

A comprehensive presentation of generalized additive models for location, scale and shape linking methods with diverse applications.

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Über die Autorinnen und Autoren

Mikis D. Stasinopoulos is Professor of Statistics at the School of Computing and Mathematical Sciences, University of Greenwich. He is, together with Professor Bob Rigby, coauthor of the original Royal Statistical Society article on GAMLSS. He has also coauthored three books on distributional regression, and in particular the theoretical and computational aspects of the GAMLSS framework.

Thomas Kneib is a Professor of Statistics at the University of Göttingen, Germany, where he is the Spokesperson of the interdisciplinary Centre for Statistics and Vice-Spokesperson of the Campus Institute Data Science. His main research interests include semiparametric regression, spatial statistics, and distributional regression.

Nadja Klein is Emmy Noether Research Group Leader in Statistics and Data Science and Professor for Uncertainty Quantification and Statistical Learning at TU Dortmund University and the Research Center Trustworthy Data Science and Security. Nadja is member of the Junge Akademie and associate editor for 'Biometrics, ' 'JABES, ' and 'Dependence Modeling.' Her. Her research interests include Bayesian methods, statistical and machine learning, and spatial statistics.

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