Statistical Foundations of Actuarial Learning and its Applications
1st ed. 2023
Book Details
Format
Hardback or Cased Book
Book Series
Springer Actuarial
ISBN-10
3031124081
ISBN-13
9783031124082
Edition
1st ed. 2023
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Nov 23rd, 2022
Print length
605 Pages
Weight
1,068 grams
Dimensions
16.20 x 24.40 x 4.20 cms
Ksh 8,100.00
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This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future.
- 1. Introduction. - 2. Exponential Dispersion Family. - 3. Estimation Theory. - 4. Predictive Modeling and Forecast Evaluation. - 5. Generalized Linear Models. - 6. Bayesian Methods, Regularization and Expectation-Maximization. - 7. Deep Learning. - 8. Recurrent Neural Networks. - 9. Convolutional Neural Networks. - 10. Natural Language Processing. - 11. Selected Topics in Deep Learning. - 12. Appendix A: Technical Results on Networks. - 13. Appendix B: Data and Examples.
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