e-Book Notes and Exercises for Cas/Soa Course 4: Loss Model Estimation, Credibility Theory and Simulation download
by Samuel Cox
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Loss Model Estimation, Credibility Theory and Simulation.
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By (author) Samuel H. Cox, By (author) R. Dale Hall.
The first approach to credibility estimation that we consider is "Limited Fluctuation Credibility", also called "classical credibility", and does not involve any Bayesian component.
Loss Models contains a wealth of examples that highlight the real-world applications of the concepts presented, and puts the emphasis on calculations and spreadsheet implementation. Parametric, non-parametric, and Bayesian estimation methods are thoroughly covered. In addition, the authors offer practical advice for choosing an appropriate model
The book covers the subject of Credibility Theory extensively and includes most aspects of this topic from the simplest case to the most general .
The book covers the subject of Credibility Theory extensively and includes most aspects of this topic from the simplest case to the most general dynamic model.
Credibility theory is a form of statistical inference used to forecast an uncertain future event developed by Thomas Bayes. It may be used when you have multiple estimates of a future event, and you would like to combine these estimates in such a way to get a more accurate and relevant estimate. This is typically used by actuaries working for insurance companies when determining the premium values.
I love the practical questions, case studies, and exercises. The authors are wonderful writers.
As someone who has frequently taught measurement courses, I am a firm believer that student learning of the material is critically tied to being able to apply the core techniques. This book provides tremendous opportunities for application of fundamental measurement concepts and techniques in all key aspects of the test development and validation process. I love the practical questions, case studies, and exercises.
Zedda approaches these simulation methods logically by providing the basic building blocks of modeling and simulation, and then delving further into the individual techniques that make up a systems model. The book concludes with an appendix that features real-world datasets and models.
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