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Effective Statistical Learning Methods for Actuaries I

Effective Statistical Learning Methods for Actuaries I This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility,…

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Springer Nature Switzerland AG

Specifikacia Effective Statistical Learning Methods for Actuaries I


Effective Statistical Learning Methods for Actuaries I

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). Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). In order to deal with tail events, analytical tools from Extreme Value Theory are presented.

The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The technical prerequisites are kept at a reasonable level in order to reach a broad readership.

Effective Statistical Learning Methods for Actuaries I patrí medzi produkty, ktoré ponúkajú vyvážený pomer kvality a ceny. V hornej časti stránky nájdeš hlavný prehľad, nižšie podrobné vlastnosti a technické parametre.

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.

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