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Effective Statistical Learning Methods for Actuaries I

Name: Effective Statistical Learning Methods for Actuaries I
Brand: Springer Nature Switzerland AG
SKU: 24519041
Price: 21186 HUF
Availability: InStock
Author: Michel Denuit
ISBN: 9783030258191

GLMs and Extensions

Michel Denuit

Donatien Hainaut

Julien Trufin

Language

English

Book Paperback

Libristo code: 24519041

Publishers Springer Nature Switzerland AG, September 2019

This book summarizes the state of the art in generalized linear models (GLMs) and their various exte... Full description

Libristo code: 24519041

146 b

21 186 Ft

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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.