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Generalized Poisson Models and their Applications in Insurance and Finance: (Modern Probability & Statistics)

Generalized Poisson Models and their Applications in Insurance and Finance: (Modern Probability & Statistics)

          
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About the Book

The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.

Table of Contents:
Basic notions of probability theory random variables, their distributions and moments; generating and characteristic functions; random vectors; stochastic independence; weak convergence of random variables and distribution functions; Poisson theorem; law of large numbers; central limit theorem; stable laws; the Berry-Esseen inequality; asymptotic expansions in the central limit theorem; elementary properties of random sums; stochastic processes; Poisson process; the definition and elementary properties of a Poisson process; Poisson process as a model of chaotic displacement of points in time; the asymptotic normality of a Poisson process; elementary rarefaction of renewal processes; convergence of superpositions of independent stochastic processes; characteristic features of the problem; approximation of distributions of randomly indexed random sequences by special mixtures; the transfer theorem; relations between the limit laws for random sequences with random and non-random indices; necessary and sufficient conditions for the convergence of distributions of random sequences with independent random indices; convergence of distributions of randomly indexed sequences to identifiable location or scale mixtures; the asymptotic behaviour of extremal random sums; convergence of distributions of random sums; the central limit theorem and the law of large numbers for random sums; a general theorem on the asymptotic behaviour of superpositions of independent stochastic processes; the transfer theorem for random sums of independent identically distributed random variables in the double array limit scheme; compound Poisson distribution; mixed and compound Poisson distributions; discrete compound Poisson distributions; the asymptotic normality of compound Poisson distributions; the Berry-Esseen inequality for Poisson random sums; non-central Lyapunov fractions; asymptotic expansions for compound Poisson distributions; the asymptotic expansions for the quantiles of compound Poisson distributions; exponential inequalities for the probabilities of large derivations of Poisson random sums; an analog of Bernshtein-Kolmogorov inequality; the application of Esscher transforms to the approximation of the tails of compound Poisson distributions; estimates of convergence rate in local limit theorems for Poisson random sums; classical risk processes; the definition of the classical risk process - its asymptotic normality; the Pollaczek-Khinchin-Beekman formula for the ruin probability in the classical risk process; approximations for the ruin probability with small safety loading; asymptotic expansions for the ruin probability with small safety loading; approximations for the ruin probability; asymptotic approximations for the distributions of the surplus in general risk processes; a problem of inventory control; a non-classical problem of optimization of the initial capital; doubly stochastic Poisson processes (Cox processes); the asymptotic behaviour of random sums


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Product Details
  • ISBN-13: 9789067643665
  • Publisher: Brill
  • Publisher Imprint: VSP International Science Publishers
  • Height: 240 mm
  • No of Pages: 453
  • Series Title: Modern Probability & Statistics
  • Weight: 830 gr
  • ISBN-10: 9067643661
  • Publisher Date: 25 Jul 2002
  • Binding: Hardback
  • Language: English
  • Returnable: N
  • Spine Width: 25 mm
  • Width: 167 mm


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