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Generalized Additive Models for Location, Scale and Shape
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A Distributional Regression Approach, with Applications
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
Artikel-Nr:
9781009410069
Veröffentl:
2024
Erscheinungsdatum:
29.02.2024
Seiten:
306
Autor:
Andreas Mayr
Gewicht:
760 g
Format:
259x186x26 mm
Sprache:
Englisch
Beschreibung:
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.
"This text provides a state-of-the-art treatment of distributional regression, accompanied by real-world examples from diverse areas of application. Maximum likelihood, Bayesian and machine learning approaches are covered in-depth and contrasted, providing an integrated perspective on GAMLSS for researchers in statistics and other data-rich fields"--
Preface; Notation and Termanology; Part I. Introduction and Basics: 1. Distributional Regression Models; 2. Distributions; 3. Additive Model Terms; Part II. Statistical Inference in GAMLSS: 4. Inferential Methods; 5. Penalized Maximum Likelihood Inference; 6. Bayesian Inference; 7. Statistical Boosting for GAMLSS; Part. III Applications and Case Studies: 8. Fetal Ultrasound; 9. Speech Intelligibility Testing; 10. Social Media Post Performance; 11. Childhood Undernutrition in India; 12. Socioeconomic Determinants of Federal Election Outcomes in Germany; 13. Variable Selection for Gene Expression Data; Appendix A. Continuous Distributions; Appendix B. Discrete Distributions; Bibliography; Index.