2011
DOI: 10.1017/s0021900200007889
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Hitting Times and the Running Maximum of Markovian Growth-Collapse Processes

Abstract: We consider a Markovian growth collapse process on the state space E = [0, ∞) which evolves as follows. Between random downward jumps the process increases with slope one. Both the jump intensity and the jump sizes depend on the current state of the process. We are interested in the behavior of the first hitting time τ y = inf{t ≥ 0|X t = y} as y becomes large and the growth of the maximum process M t = sup{X s |0 ≤ s ≤ t} as t → ∞. We consider the recursive sequence of equations Am n = m n−1 , m 0 ≡ 1, where … Show more

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Cited by 6 publications
(3 citation statements)
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“…In this section we consider a piecewise deterministic Markov process X t with jumps that are governed by a jump measure with the generalized lack of memory property described above. See [2] and [8] for similar models.…”
Section: A Growth Collapse Process With Generalized Memoryless Jumpsmentioning
confidence: 99%
See 1 more Smart Citation
“…In this section we consider a piecewise deterministic Markov process X t with jumps that are governed by a jump measure with the generalized lack of memory property described above. See [2] and [8] for similar models.…”
Section: A Growth Collapse Process With Generalized Memoryless Jumpsmentioning
confidence: 99%
“…This leads to the final solutionf (x) = a + + − a − e a − (x−z * (θ)) + c − a − a + − a − e a + (x−z * (θ)). This example is a generalization of Example (A), Section 4.1 in[8]. Suppose that the jump measure ν(x, y) = s θ (y)/s θ (x) is defined such that for some α > 0 s θ (x)λ(x) = ακ(x).…”
mentioning
confidence: 99%
“…Piecewise deterministic paths can be observed for Markov processes in a variety of applications. We mention risk process ( [1,48,19,20,25]), growth collapse and stress release models ( [9,53,58,12,41]), queueing models ( [14,11]), earthquake models ( [46]), repairable systems ( [38]), storage models ( [15,27,28]) and TCP data transmission ( [39,40,24]). The mathematical framework that is used in this paper was introduced by Davis [22,21].…”
Section: Introductionmentioning
confidence: 99%