Generalized Linear Models for Insurance Data

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Author :
Publisher : Cambridge University Press
ISBN 13 : 1139470477
Total Pages : 207 pages
Book Rating : 4.76/5 ( download)

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Book Synopsis Generalized Linear Models for Insurance Data by : Piet de Jong

Download or read book Generalized Linear Models for Insurance Data written by Piet de Jong and published by Cambridge University Press. This book was released on 2008-02-28 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.

Non-Life Insurance Pricing with Generalized Linear Models

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Publisher : Springer Science & Business Media
ISBN 13 : 3642107915
Total Pages : 181 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Non-Life Insurance Pricing with Generalized Linear Models by : Esbjörn Ohlsson

Download or read book Non-Life Insurance Pricing with Generalized Linear Models written by Esbjörn Ohlsson and published by Springer Science & Business Media. This book was released on 2010-03-18 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-life insurance pricing is the art of setting the price of an insurance policy, taking into consideration varoius properties of the insured object and the policy holder. Introduced by British actuaries generalized linear models (GLMs) have become today a the standard aproach for tariff analysis. The book focuses on methods based on GLMs that have been found useful in actuarial practice and provides a set of tools for a tariff analysis. Basic theory of GLMs in a tariff analysis setting is presented with useful extensions of standarde GLM theory that are not in common use. The book meets the European Core Syllabus for actuarial education and is written for actuarial students as well as practicing actuaries. To support reader real data of some complexity are provided at www.math.su.se/GLMbook.

Generalized Linear Models for Insurance Rating

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Publisher :
ISBN 13 : 9780996889728
Total Pages : 106 pages
Book Rating : 4.28/5 ( download)

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Book Synopsis Generalized Linear Models for Insurance Rating by : Mark Goldburd

Download or read book Generalized Linear Models for Insurance Rating written by Mark Goldburd and published by . This book was released on 2016-06-08 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Generalized Linear Models for Insurance Data

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Author :
Publisher : Cambridge University Press
ISBN 13 :
Total Pages : 206 pages
Book Rating : 4./5 ( download)

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Book Synopsis Generalized Linear Models for Insurance Data by :

Download or read book Generalized Linear Models for Insurance Data written by and published by Cambridge University Press. This book was released on with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance

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Publisher : Cambridge University Press
ISBN 13 : 1316720527
Total Pages : 337 pages
Book Rating : 4.23/5 ( download)

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Book Synopsis Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance by : Edward W. Frees

Download or read book Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance written by Edward W. Frees and published by Cambridge University Press. This book was released on 2016-07-27 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.

Regression Modeling with Actuarial and Financial Applications

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Publisher : Cambridge University Press
ISBN 13 : 0521760119
Total Pages : 585 pages
Book Rating : 4.19/5 ( download)

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Book Synopsis Regression Modeling with Actuarial and Financial Applications by : Edward W. Frees

Download or read book Regression Modeling with Actuarial and Financial Applications written by Edward W. Frees and published by Cambridge University Press. This book was released on 2010 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.

Generalized Linear Models

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Author :
Publisher : Routledge
ISBN 13 : 1351445847
Total Pages : 361 pages
Book Rating : 4.49/5 ( download)

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Book Synopsis Generalized Linear Models by : P. McCullagh

Download or read book Generalized Linear Models written by P. McCullagh and published by Routledge. This book was released on 2019-01-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and ot

Effective Statistical Learning Methods for Actuaries I

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Publisher : Springer Nature
ISBN 13 : 3030258203
Total Pages : 441 pages
Book Rating : 4.07/5 ( download)

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Book Synopsis Effective Statistical Learning Methods for Actuaries I by : Michel Denuit

Download or read book Effective Statistical Learning Methods for Actuaries I written by Michel Denuit and published by Springer Nature. This book was released on 2019-09-03 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modern Actuarial Risk Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 3540867368
Total Pages : 394 pages
Book Rating : 4.64/5 ( download)

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Book Synopsis Modern Actuarial Risk Theory by : Rob Kaas

Download or read book Modern Actuarial Risk Theory written by Rob Kaas and published by Springer Science & Business Media. This book was released on 2008-12-03 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and.

Stochastic Loss Reserving Using Generalized Linear Models

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Publisher :
ISBN 13 : 9780996889704
Total Pages : 100 pages
Book Rating : 4.01/5 ( download)

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Book Synopsis Stochastic Loss Reserving Using Generalized Linear Models by : Greg Taylor

Download or read book Stochastic Loss Reserving Using Generalized Linear Models written by Greg Taylor and published by . This book was released on 2016-05-04 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph, authors Greg Taylor and Gráinne McGuire discuss generalized linear models (GLM) for loss reserving, beginning with strong emphasis on the chain ladder. The chain ladder is formulated in a GLM context, as is the statistical distribution of the loss reserve. This structure is then used to test the need for departure from the chain ladder model and to consider natural extensions of the chain ladder model that lend themselves to the GLM framework.