Interactive Features of Loss Data Analytics
Preface
1
Introduction to Interactive Features
1.1
Active Learning
1.2
LDA Interactive Features
1.2.1
What we Have
1.2.2
In Process
1.2.3
Plans for Future Work
1.3
LDA Non-Interactive Features
2
End of Section Quizzes
2.1
1. Introduction to Loss Data Analytics
2.1.1
Section 1.1
2.1.2
Section 1.2
2.1.3
Section 1.3
2.2
2. Frequency Modeling
2.2.1
Section 2.1
2.2.2
Section 2.2
2.2.3
Section 2.3
2.2.4
Section 2.4
2.2.5
Section 2.5
2.2.6
Section 2.6
2.2.7
Section 2.7
2.3
3. Modeling Loss Severity
2.3.1
Section 3.1
2.3.2
Section 3.2
2.3.3
Section 3.3
2.3.4
Section 3.4
2.3.5
Section 3.5
2.4
4. Model Selection and Estimation
2.4.1
Section 4.1
2.4.2
Section 4.2
2.4.3
Section 4.3
2.4.4
Section 4.4
2.5
5. Aggregate Loss Models
2.5.1
Section 5.1
2.5.2
Section 5.2
2.5.3
Section 5.3
2.5.4
Section 5.4
2.5.5
Section 5.5
2.6
8. Risk Classification
2.6.1
Section 8.1
2.6.2
Section 8.2
2.6.3
Section 8.3
2.7
9. Experience Rating Using Credibility Theory
2.7.1
Section 9.1
2.7.2
Section 9.2
2.7.3
Section 9.3
2.7.4
Section 9.6
2.8
10. Insurance Portfolio Management including Reinsurance
2.8.1
Section 10.1
2.8.2
Section 10.2
2.8.3
Section 10.3
2.9
13. Data and Systems
2.9.1
Section 13.1
2.9.2
Section 13.2
2.9.3
Section 13.3
2.10
14. Dependence Modeling
2.10.1
Section 14.1
2.10.2
Section 14.2
2.10.3
Section 14.3
2.10.4
Section 14.5
2.10.5
Section 14.6
3
Exercises
3.1
The Issue
3.2
Wordpress Exercises
3.2.1
2. Frequency Modeling
3.2.2
3. Modeling Loss Severity
3.2.3
4. Model Selection and Estimation
3.2.4
5. Aggregate Loss Models
4
Statistical Code
Interactive Features of LDA on GitHub
Interactive Features of Loss Data Analytics
Chapter 2
End of Section Quizzes
2.1
1. Introduction to Loss Data Analytics
2.1.1
Section 1.1
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2.1.2
Section 1.2
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2.1.3
Section 1.3
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2.2
2. Frequency Modeling
2.2.1
Section 2.1
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2.2.2
Section 2.2
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2.2.3
Section 2.3
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2.2.4
Section 2.4
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2.2.5
Section 2.5
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2.2.6
Section 2.6
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2.2.7
Section 2.7
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2.3
3. Modeling Loss Severity
2.3.1
Section 3.1
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2.3.2
Section 3.2
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2.3.3
Section 3.3
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2.3.4
Section 3.4
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2.3.5
Section 3.5
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2.4
4. Model Selection and Estimation
2.4.1
Section 4.1
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2.4.2
Section 4.2
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2.4.3
Section 4.3
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2.4.4
Section 4.4
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2.5
5. Aggregate Loss Models
2.5.1
Section 5.1
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2.5.2
Section 5.2
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2.5.3
Section 5.3
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2.5.4
Section 5.4
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2.5.5
Section 5.5
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2.6
8. Risk Classification
2.6.1
Section 8.1
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2.6.2
Section 8.2
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2.6.3
Section 8.3
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2.7
9. Experience Rating Using Credibility Theory
2.7.1
Section 9.1
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2.7.2
Section 9.2
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2.7.3
Section 9.3
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2.7.4
Section 9.6
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2.8
10. Insurance Portfolio Management including Reinsurance
2.8.1
Section 10.1
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2.8.2
Section 10.2
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2.8.3
Section 10.3
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2.9
13. Data and Systems
2.9.1
Section 13.1
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2.9.2
Section 13.2
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2.9.3
Section 13.3
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2.10
14. Dependence Modeling
2.10.1
Section 14.1
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2.10.2
Section 14.2
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2.10.3
Section 14.3
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2.10.4
Section 14.5
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2.10.5
Section 14.6
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