Effective Statistical Learning Methods for Actuaries I GLMs and Extensions /

• Κύριοι συγγραφείς: Denuit, Michel (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Hainaut, Donatien (http://id.loc.gov/vocabulary/relators/aut), Trufin, Julien (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Springer Actuarial Lecture Notes,
• Θέματα: Actuarial science.; Statistics .; Actuarial Sciences.; Statistics for Business, Management, Economics, Finance, Insurance.

This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling,...