Effective Statistical Learning Methods For Actuaries
Download and Read Effective Statistical Learning Methods For Actuaries full books in PDF, ePUB, and Kindle. Read online free Effective Statistical Learning Methods For Actuaries ebook anywhere anytime directly on your device. We cannot guarantee that every ebooks is available!
Effective Statistical Learning Methods for Actuaries I
Author | : Michel Denuit |
Publisher | : Springer Nature |
Total Pages | : 441 |
Release | : 2019-09-03 |
Genre | : Business & Economics |
ISBN | : 3030258203 |
Download Effective Statistical Learning Methods for Actuaries I Book in PDF, Epub and Kindle
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, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.
Effective Statistical Learning Methods for Actuaries I Related Books
Pages: 441
Pages: 250
Pages: 228
Pages:
Pages: 441