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Asymptotic Expansions for Infinite Weighted Convolutions of Heavy Tail Distributions and Applications [Pehme köide]

Teised raamatud teemal:
Teised raamatud teemal:
The authors establish some asymptotic expansions for infinite weighted convolution of distributions having regularly varying tails. Applications to linear time series models, tail index estimation, compound sums, queueing theory, branching processes, infinitely divisible distributions and implicit transient renewal equations are given.A noteworthy feature of the approach taken in this paper is that through the introduction of objects, which the authors call the Laplace characters, a link is established between tail area expansions and algebra. By virtue of this representation approach, a unified method to establish expansions across a variety of problems is presented and, moreover, the method can be easily programmed so that a computer algebra package makes implementation of the method not only feasible but simple.
Introduction
1(8)
Prolegomenom
1(3)
Mathematical overview and heuristics
4(5)
Main result
9(12)
Some notation
9(1)
Asymptotic scales
10(2)
The Laplace characters
12(3)
Smoothly varying functions of finite order
15(1)
Asymptotic expansion for infinite weighted convolution
16(5)
Implementing the expansion
21(18)
How many terms are in the expansion?
21(3)
Asymptotic scales and functions of class m
24(3)
Tail calculus: From Laplace characters to linear algebra
27(1)
Some examples
28(6)
Two terms expansion and second order regular variation
34(2)
Some open questions
36(3)
Applications
39(26)
ARMA models
39(1)
Tail index estimation
40(7)
Randomly weighted sums
47(3)
Compound sums
50(3)
Queueing theory
53(2)
Branching processes
55(1)
Infinitely divisible distributions
56(2)
Implicit transient renewal equation and iterative systems
58(7)
Preparing the proof
65(10)
Properties of Laplace characters
65(2)
Properties of smoothly varying functions of finite order
67(8)
Proof in the positive case
75(22)
Decomposition of the convolution into integral and multiplication operators
75(2)
Organizing the proof
77(2)
Regular variation and basic tail estimates
79(3)
The fundamental estimate
82(1)
Basic lemmas
83(6)
Inductions
89(5)
Conclusion
94(3)
Removing the sign restriction on the random variables
97(8)
Elementary properties of UH
98(1)
Basic expansion of UH
99(1)
A technical lemma
100(2)
Conditional expansion and removing conditioning
102(3)
Removing the sign restriction on the constants
105(4)
Neglecting terms involving the multiplication operators
105(2)
Substituting H(k) and G(k) by their expansions
107(2)
Removing the smoothness restriction
109(2)
Appendix. Maple code 111(4)
Bibliography 115