Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Mode

Description: Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques by Edward W. Frees, Richard A. Derrig, Glenn Meyers This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description Predictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data. Table of Contents 1. Predictive modeling in actuarial science Edward W. Frees and Richard A. Derrig; Part I. Predictive Modeling Foundations: 2. Overview of linear models Marjorie Rosenberg; 3. Regression with categorical dependent variables Montserrat Guillen; 4. Regression with count-dependent variables Jean-Philippe Boucher; 5. Generalized linear models Curtis Gary Dean; 6. Frequency and severity models Edward W. Frees; Part II. Predictive Modeling Methods: 7. Longitudinal and panel data models Edward W. Frees; 8. Linear mixed models Katrien Antonio and Yanwei Zhang; 9. Credibility and regression modeling Vytaras Brazauskas, Harald Dornheim and Ponmalar Ratnam; 10. Fat-tailed regression models Peng Shi; 11. Spatial modeling Eike Brechmann and Claudia Czado; 12. Unsupervised learning Louise Francis; Part III. Bayesian and Mixed Modeling: 13. Bayesian computational methods Brian Hartman; 14. Bayesian regression models Luis Nieto-Barajas and Enrique de Alba; 15. Generalized additive models and nonparametric regression Patrick L. Brockett, Shuo-Li Chuang and Utai Pitaktong; 16. Non-linear mixed models Katrien Antonio and Yanwei Zhang; Part IV. Longitudinal Modeling: 17. Time series analysis Piet de Jong; 18. Claims triangles/loss reserves Greg Taylor; 19. Survival models Jim Robinson; 20. Transition modeling Bruce Jones and Weijia Wu. Review With contributions coming from a wide variety of researchers, professors, and actuaries - including several CAS Fellows - its clear that this book will be valuable for any P and C actuary whose main concern is using predictive modeling in his or her own work. David Zornek, Actuarial Review Promotional This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling. Review Quote "With contributions coming from a wide variety of researchers, professors, and actuaries - including several CAS Fellows - its clear that this book will be valuable for any P and C actuary whose main concern is using predictive modeling in his or her own work." David Zornek, Actuarial Review Promotional "Headline" This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling. Description for Bookstore This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. It emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data. Description for Library This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. It emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data. Details ISBN1107029872 Publisher Cambridge University Press Year 2014 ISBN-10 1107029872 ISBN-13 9781107029873 Format Hardcover Imprint Cambridge University Press Place of Publication Cambridge Country of Publication United Kingdom Edited by Glenn Meyers DEWEY 368.01 Media Book Publication Date 2014-07-28 Pages 563 Short Title PREDICTIVE MODELING APPLICATIO Language English Affiliation Temple University, Philadelphia Illustrations Worked examples or Exercises; 94 Tables, unspecified; 120 Line drawings, unspecified UK Release Date 2014-07-28 AU Release Date 2014-07-28 NZ Release Date 2014-07-28 Author Glenn Meyers Series International Series on Actuarial Science Alternative 9781139342674 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:168634306;

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