Statistical Methods with Applications to Demography and Life Insurance

Table of contents

1. Front Cover
2. Contents
3. Preface
4. List of Figures
5. List of Tables
6. Lecture 1: Duration of life as a random variable (1/2)
7. Lecture 1: Duration of life as a random variable (2/2)
8. Lecture 2: Models of distribution functions F(x) and force of mortality μ(x) (1/3)
9. Lecture 2: Models of distribution functions F(x) and force of mortality μ(x) (2/3)
10. Lecture 2: Models of distribution functions F(x) and force of mortality μ(x) (3/3)
11. Lecture 3: The empirical distribution function of duration of life (1/2)
12. Lecture 3: The empirical distribution function of duration of life (2/2)
13. Lecture 4: Deviation of Fn(x) from F(x) as a random process (1/2)
14. Lecture 4: Deviation of Fn(x) from F(x) as a random process (2/2)
15. Lecture 5: Limit of empirical process: Brownian bridge. Distribution of X2 goodness of fit statistic (1/3)
16. Lecture 5: Limit of empirical process: Brownian bridge. Distribution of X2 goodness of fit statistic (2/3)
17. Lecture 5: Limit of empirical process: Brownian bridge. Distribution of X2 goodness of fit statistic (3/3)
18. Lecture 6: Statistical consequences of what we have learned so far. Two-sample problems (1/3)
19. Lecture 6: Statistical consequences of what we have learned so far. Two-sample problems (2/3)
20. Lecture 6: Statistical consequences of what we have learned so far. Two-sample problems (3/3)
21. Lecture 7: Testing parametric hypotheses. Unexpected example – exponentiality of durations of rule of Roman emperors (1/4)
22. Lecture 7: Testing parametric hypotheses. Unexpected example – exponentiality of durations of rule of Roman emperors (2/4)
23. Lecture 7: Testing parametric hypotheses. Unexpected example – exponentiality of durations of rule of Roman emperors (3/4)
24. Lecture 7: Testing parametric hypotheses. Unexpected example – exponentiality of durations of rule of Roman emperors (4/4)
25. Lecture 8: Estimation of the rate of mortality (1/2)
26. Lecture 8: Estimation of the rate of mortality (2/2)
27. Lecture 9: Censored observations. Related point processes (1/2)
28. Lecture 9: Censored observations. Related point processes (2/2)
29. Lecture 10: Kaplan–Meier estimator (product-limit estimator) for F (1/3)
30. Lecture 10: Kaplan–Meier estimator (product-limit estimator) for F (2/3)
31. Lecture 10: Kaplan–Meier estimator (product-limit estimator) for F (3/3)
32. Lecture 11: Statistical inference about F, based on the Kaplan–Meier estimator (1/4)
33. Lecture 11: Statistical inference about F, based on the Kaplan–Meier estimator (2/4)
34. Lecture 11: Statistical inference about F, based on the Kaplan–Meier estimator (3/4)
35. Lecture 11: Statistical inference about F, based on the Kaplan–Meier estimator (4/4)
36. Lecture 12: Life insurance and net premiums (1/4)
37. Lecture 12: Life insurance and net premiums (2/4)
38. Lecture 12: Life insurance and net premiums (3/4)
39. Lecture 12: Life insurance and net premiums (4/4)
40. Lecture 13: More on net premiums. Endowments and annuities (1/2)
41. Lecture 13: More on net premiums. Endowments and annuities (2/2)
42. Lecture 14: Annuities certain. Some problems of general theory (1/2)
43. Lecture 14: Annuities certain. Some problems of general theory (2/2)
44. Lecture 15: Right-tail behavior of Fn. Non-parametric confidence bounds for expected remaining life (1/5)
45. Lecture 15: Right-tail behavior of Fn. Non-parametric confidence bounds for expected remaining life (2/5)
46. Lecture 15: Right-tail behavior of Fn. Non-parametric confidence bounds for expected remaining life (3/5)
47. Lecture 15: Right-tail behavior of Fn. Non-parametric confidence bounds for expected remaining life (4/5)
48. Lecture 15: Right-tail behavior of Fn. Non-parametric confidence bounds for expected remaining life (5/5)
49. Lecture 16: Population dynamics (1/4)
50. Lecture 16: Population dynamics (2/4)
51. Lecture 16: Population dynamics (3/4)
52. Lecture 16: Population dynamics (4/4)
53. Bibliography (1/2)
54. Bibliography (2/2)