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...
Gorde:
| Egile nagusia: | |
|---|---|
| Formatua: | Livre numérique |
| Hizkuntza: | Anglais |
| Argitaratua: |
Les Ulis :
EDP Sciences
2024.
Paris : Cyberlibris |
| Sarrera elektronikoa: | Accès Université d'Orléans et IFPM Accès INSA CVL |
| Oharra: |
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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| 009 | PPN283329327 | ||
| 020 | |a 9782759837205 | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Tian, Maozai. | |
| 245 | 1 | 0 | |a Hierarchical Quantile Modeling : |b Theory, Methodology and Applications |c Maozai Tian. |
| 260 | |a Les Ulis : |b EDP Sciences. | ||
| 260 | |a Paris : |b Cyberlibris, |c 2024. | ||
| 500 | |a Couverture. https://static2.cyberlibris.com/books_upload/136pix/9782759837205.jpg | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur | ||
| 506 | |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris | ||
| 520 | |a 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 | ||
| 710 | 2 | |a EDP Sciences. |4 pbl | |
| 776 | 0 | |t Hierarchical Quantile Modeling |o Theory, Methodology and Applications |f Maozai Tian |c Les Ulis |n EDP Sciences |d 2024 |p 1 vol. (754 p.) |z 978-27-5983-719-9 | |
| 856 | 4 | |5 452349901:873401360 |u https://ezproxy.univ-orleans.fr/login?qurl=https://univ.scholarvox.com/book/88960847 |z Accès Université d'Orléans et IFPM | |
| 856 | 4 | |5 180339901:87359410X |u https://ezproxy.insa-cvl.fr/login?qurl=https://univ.scholarvox.com/book/88960847 |z Accès INSA CVL | |
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