Hierarchical Quantile Modeling : Theory, Methodology and Applications

This book offers a concise and comprehensive introduction to Hierarchical Quantile Modeling, a modern statistical methodology that extends traditional hierarchical models and quantile regression techniques to analyze complex data structures often found in fields like biology, economics, and educatio...

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Hlavní autor: Tian, Maozai
Médium: Livre numérique
Jazyk:Anglais
Vydáno: Les Ulis : EDP Sciences 2024.
Paris : Cyberlibris
On-line přístup:Accès Université d'Orléans et IFPM
Accès INSA CVL
Poznámka: Couverture. https://static2.cyberlibris.com/books_upload/136pix/9782759837205.jpg
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Hierarchical Quantile Modeling, Theory, Methodology and Applications, Maozai Tian, Les Ulis, EDP Sciences, 2024, 1 vol. (754 p.), 978-27-5983-719-9
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Shrnutí:This book offers a concise and comprehensive introduction to Hierarchical Quantile Modeling, a modern statistical methodology that extends traditional hierarchical models and quantile regression techniques to analyze complex data structures often found in fields like biology, economics, and education. Unlike classic models, Hierarchical Quantile Modeling accommodates heteroscedasticity and nonparametric relationships, allowing for a detailed study of the entire conditional distribution of a response variable. The book is structured in four parts: an introduction to hierarchical modeling, a detailed look at quantile regression, an in-depth exploration of Hierarchical Quantile Modeling, and practical applications using real-world hierarchical, repeated, and clustered data. Drawing on the author's decade-long experience in research and teaching, this guide is ideal for graduate students, researchers, and practitioners. It includes examples and software guidance using R, S-plus, SAS, and SPSS, making it a valuable resource for anyone interested in advanced statistical analysis
Popis jednotky:Couverture. https://static2.cyberlibris.com/books_upload/136pix/9782759837205.jpg
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
ISBN:9782759837205
Přístup:L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris