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Applied probability meets Bessel, Hermite, Kummer, Tricomi, Wiener & Hopf (and also Ornstein & Uhlenbeck) Boxma, Onno
Description
We discuss a few applied probability models: a blood bank model, an insurance risk model and a queueing/inventory model. In each case, the process under study {X(t), t ≥ 0} has state space (−∞, ∞). In the blood bank case, X(t) indicates the amount of blood present at time t, if there is a positive amount present; otherwise, −X(t) denotes the total amount that is being demanded. In the insurance risk case, X(t) indicates the capital at time t, if there is a positive amount present; otherwise, −X(t) denotes the shortage. It is agreed that ruin does not immediately occur when X(t) becomes negative, but the process ends (bankruptcy) according to a bankruptcy rate function ω(−X(t)) when X(t) < 0. In the queueing/inventory model, X(t) indicates the amount of work present at time t, if there is a positive amount present; if no work is present, the tireless server keeps working, building up an inventory, and −X(t) then denotes the inventory level. The inventory is removed at a rate ω(−X(t)). Under Poisson assumptions for the various arrival processes (of blood donations and blood requirements; of claims; of service requirements) and ergodicity conditions we try to determine the steady-state distributions of the X(t) processes; in the insurance risk model, we determine the bankruptcy probability. This appears to involve various special functions, like those of Bessel, Hermite, Kummer and Tricomi.
Item Metadata
Title |
Applied probability meets Bessel, Hermite, Kummer, Tricomi, Wiener & Hopf (and also Ornstein & Uhlenbeck)
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2015-06-04T13:33
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Description |
We discuss a few applied probability models: a blood bank model, an insurance risk model and a queueing/inventory model. In each case, the process under study {X(t), t ≥ 0} has state space (−∞, ∞).
In the blood bank case, X(t) indicates the amount of blood present at time t, if there is a positive amount present; otherwise, −X(t) denotes the total amount that is being demanded.
In the insurance risk case, X(t) indicates the capital at time t, if there is a positive amount present; otherwise, −X(t) denotes the shortage. It is agreed that ruin does not immediately occur when X(t) becomes negative, but the process ends (bankruptcy) according to a bankruptcy rate function ω(−X(t)) when X(t) < 0.
In the queueing/inventory model, X(t) indicates the amount of work present at time t, if there is a positive amount present; if no work is present, the tireless server keeps working, building up an inventory, and −X(t) then denotes the inventory level. The inventory is removed at a rate ω(−X(t)).
Under Poisson assumptions for the various arrival processes (of blood donations and blood requirements; of claims; of service requirements) and ergodicity conditions we try to determine the steady-state distributions of the X(t) processes; in the insurance risk model, we determine the bankruptcy probability. This appears to involve various special functions, like those of Bessel, Hermite, Kummer and Tricomi.
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Extent |
58 minutes
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Subject | |
Type | |
File Format |
video/mp4
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Language |
eng
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Notes |
Author affiliation: Eindhoven University of Technology
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Series | |
Date Available |
2016-01-04
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0221665
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada