Statistical Methods with Applications to Demography and Life Insurance
eBook - PDF

Statistical Methods with Applications to Demography and Life Insurance

  1. 242 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Statistical Methods with Applications to Demography and Life Insurance

About this book

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, Statistical Methods with Applications to Demography and Life Insurance presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature.

The book mainly focuses on the analysis of an individual life and describes statistical methods based on empirical and related processes. Coverage ranges from analyzing the tails of distributions of lifetimes to modeling population dynamics with migrations. To help readers understand the technical points, the text covers topics such as the Stieltjes, Wiener, and Ito integrals. It also introduces other themes of interest in demography, including mixtures of distributions, analysis of longevity and extreme value theory, and the age structure of a population. In addition, the author discusses net premiums for various insurance policies.

Mathematical statements are carefully and clearly formulated and proved while avoiding excessive technicalities as much as possible. The book illustrates how these statements help solve numerous statistical problems. It also includes more than 70 exercises.

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Yes, you can access Statistical Methods with Applications to Demography and Life Insurance by Estate V. Khmaladze in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

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
  7. Lecture 2: Models of distribution functions F(x) and force of mortality μ(x)
  8. Lecture 3: The empirical distribution function of duration of life
  9. Lecture 4: Deviation of Fn(x) from F(x) as a random process
  10. Lecture 5: Limit of empirical process: Brownian bridge. Distribution of X2 goodness of fit statistic
  11. Lecture 6: Statistical consequences of what we have learned so far. Two-sample problems
  12. Lecture 7: Testing parametric hypotheses. Unexpected example – exponentiality of durations of rule of Roman emperors
  13. Lecture 8: Estimation of the rate of mortality
  14. Lecture 9: Censored observations. Related point processes
  15. Lecture 10: Kaplan–Meier estimator (product-limit estimator) for F
  16. Lecture 11: Statistical inference about F, based on the Kaplan–Meier estimator
  17. Lecture 12: Life insurance and net premiums
  18. Lecture 13: More on net premiums. Endowments and annuities
  19. Lecture 14: Annuities certain. Some problems of general theory
  20. Lecture 15: Right-tail behavior of Fn. Non-parametric confidence bounds for expected remaining life
  21. Lecture 16: Population dynamics
  22. Bibliography