Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques
eBook - PDF

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

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

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

About this book

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.

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Yes, you can access Predictive Modeling Applications in Actuarial Science: Volume 1, Predictive Modeling Techniques by Edward W. Frees,Richard A. Derrig,Glenn Meyers in PDF and/or ePUB format, as well as other popular books in Economia & Statistiche per il settore aziendale ed economico. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half title
  3. Series
  4. Title
  5. Copyright
  6. Contents
  7. Contributor List
  8. Acknowledgments
  9. 1 Predictive Modeling in Actuarial Science
  10. I Predictive Modeling Foundations
  11. II Predictive Modeling Methods
  12. III Bayesian and Mixed Modeling
  13. IV Longitudinal Modeling
  14. Index