Download e-book for kindle: Asymptotic Analysis of Random Walks: Heavy-Tailed by A. A. Borovkov

By A. A. Borovkov

ISBN-10: 0511721390

ISBN-13: 9780511721397

ISBN-10: 052188117X

ISBN-13: 9780521881173

This booklet specializes in the asymptotic habit of the possibilities of enormous deviations of the trajectories of random walks with 'heavy-tailed' (in specific, frequently various, sub- and semiexponential) bounce distributions. huge deviation percentages are of serious curiosity in several utilized components, standard examples being spoil chances in danger thought, blunders chances in mathematical statistics, and buffer-overflow percentages in queueing conception. The classical huge deviation idea, built for distributions decaying exponentially quickly (or even swifter) at infinity, quite often makes use of analytical tools. If the quick decay fails, that is the case in lots of vital utilized difficulties, then direct probabilistic tools frequently end up to be effective. This monograph offers a unified and systematic exposition of the massive deviation concept for heavy-tailed random walks. lots of the effects offered within the ebook are showing in a monograph for the 1st time. lots of them have been got by way of the authors.

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Extra resources for Asymptotic Analysis of Random Walks: Heavy-Tailed Distributions (Encyclopedia of Mathematics and its Applications)

Example text

21), one has V (σ) = σ −α L(σ) = L(t1/α L1/α (t1/α )) L(t1/α ) 1 ∼ = . 27). 4 is proved. f. V (t), its Laplace transform ∞ e−λt V (t) dt < ∞ ψ(λ) := 0 is defined for any λ > 0. The following asymptotic relations hold true for the transform. 5. f. e. 2)). (i) If α ∈ [0, 1) then ψ(λ) ∼ (ii) If α = 1 and ∞ 0 Γ(1 − α) V (1/λ) λ as λ ↓ 0. f. and, moreover, VI (t) as t → ∞. ∞ (iii) In any case, ψ(λ) ↑ VI (∞) = 0 V (t) dt ∞ as λ ↓ 0. 32), one obtains V (t) ∼ ψ(1/t) tΓ(1 − α) as t → ∞. f. as λ ↓ 0. Assertions of this kind are referred to as Tauberian theorems.

G(M ) G(t) t>M Since G ∈ S, for any ε > 0 there exists an M = M (ε) such that sup t>M G2∗ (t) − G(t) < 1 + ε, G(t) and hence αn b0 + αn−1 (1 + ε), b0 := 1 + 1/G(M ), α1 = 1. From here one obtains recursively n−1 αn b0 + b0 (1 + ε) + αn−2 (1 + ε)2 ··· (1 + ε)j b0 j=0 b0 (1 + ε)n . ε The theorem is proved. 2 Sufficient conditions for subexponentiality Now we will turn to a discussion of sufficient conditions for a given distribution G to belong to the class of subexponential distributions. 8) and therefore the easily verified condition G ∈ L is, quite naturally, always present in conditions sufficient for G ∈ S.

22 below, p. 29). 40) to the case when n grows together with x, and also to refining this relation for distributions with both regularly varying and semiexponential tails. 39). In the next section we will consider the main properties of these distributions. 1 The main properties of subexponential distributions Before giving any formal definitions, we will briefly describe the relationships between the classes of distributions that we are going to introduce and explain why we pay them different amounts of attention in different contexts.

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Asymptotic Analysis of Random Walks: Heavy-Tailed Distributions (Encyclopedia of Mathematics and its Applications) by A. A. Borovkov


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