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Erlang(2) Risk Process Perturbed by Diffusion

Author: LiQiuLian
Tutor: HuYiJun
School: Wuhan University
Course: Probability Theory and Mathematical Statistics
Keywords: Erlang (2) Risk Model Instantaneous surplus before bankruptcy Bankruptcy deficit Integral expression Differential Equations
CLC: O211.67
Type: Master's thesis
Year: 2005
Downloads: 60
Quote: 0
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Abstract


This dissertation research interference Erlang (2) Risk Model . Immediately before the bankruptcy surplus distribution bankruptcy deficit distribution , as well as the joint distribution of the deficit in the moments before the bankruptcy surplus and bankruptcy , and several other important quantity . In the first chapter section to be discussed with the introduction of interference Erlang (2) risk model , define the time of ruin , the surplus immediately before the bankruptcy distribution , as well as the bankruptcy deficit distribution . Distribution of the surplus immediately before the second chapter focuses on bankruptcy . In both cases , ie u gt ; x and u ≦ x case , the distribution of the surplus immediately before the bankruptcy integral expression of C ( u , x ) = 1 / 2 integral from n = 0 to ∞ [ G ( 2u ct , x) G (ct, x)] e -λt (1 λt) h (u / σ, t) dt integral from n = 0 to ∞ f λ 2 se -λs ds (?) H (u / σ, s, ω) dω integral from n = 0 to (u cs σω) G (u cs σω-z, x) dF (z) I usx integral from n = 0 to ∞ λ 2 se -λs ds integral from n = (u / σ) to (u / σ ) H ( ( u / sigma ) , s , omega ) dω integral from n = ( u cs ? ? ) to ∞ Df ( z ) in the second quarter , proved twice continuously differentiable nature , so as to immediately before the bankruptcy the differential equation of surplus distribution 1/2σ 2 G u \> < / sup > ( u , y ) 0 in the third chapter , we consider the distribution bankruptcy deficit , get the integral expression and differential equations , are as follows : D ( u , y ) = 1/2 integral from n = 0 to ∞ [D (2u ct, y) D (ct, y)] e -λt (1 λt) h (u / σ, t) dt

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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Theory of probability ( probability theory, probability theory ) > Random process > Expectations and Forecast
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