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Journal articles on the topic 'Random times'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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1

Helali, Amine, and Matthias Löwe. "Hitting times, commute times, and cover times for random walks on random hypergraphs." Statistics & Probability Letters 154 (November 2019): 108535. http://dx.doi.org/10.1016/j.spl.2019.06.011.

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2

Li, Libo, and Marek Rutkowski. "Random times and multiplicative systems." Stochastic Processes and their Applications 122, no. 5 (2012): 2053–77. http://dx.doi.org/10.1016/j.spa.2012.02.011.

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3

Chupeau, Marie, Olivier Bénichou, and Raphaël Voituriez. "Cover times of random searches." Nature Physics 11, no. 10 (2015): 844–47. http://dx.doi.org/10.1038/nphys3413.

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4

Lacaze, B. "Random propagation times in ultrasonics." Waves in Random and Complex Media 20, no. 1 (2010): 179–90. http://dx.doi.org/10.1080/17455030903501840.

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5

Barnett, Chris, and Ivan F. Wilde. "Random times and time projections." Proceedings of the American Mathematical Society 110, no. 2 (1990): 425. http://dx.doi.org/10.1090/s0002-9939-1990-1021894-9.

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6

Nakagawa, Toshio, and Xufeng Zhao. "COMPARISONS OF REPLACEMENT POLICIES WITH CONSTANT AND RANDOM TIMES." Journal of the Operations Research Society of Japan 56, no. 1 (2013): 1–14. http://dx.doi.org/10.15807/jorsj.56.1.

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7

Kochubei, Anatoly, Yuri Kondratiev, and Jose Luis Da Silva. "From random times to fractional kinetics." Мiждисциплiнарнi дослiдження складних систем, no. 16 (May 23, 2020): 5–32. http://dx.doi.org/10.31392/iscs.2020.16.005.

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8

Dupuis, Paul, and Hui Wang. "Optimal stopping with random intervention times." Advances in Applied Probability 34, no. 01 (2002): 141–57. http://dx.doi.org/10.1017/s0001867800011435.

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We consider a class of optimal stopping problems where the ability to stop depends on an exogenous Poisson signal process - we can only stop at the Poisson jump times. Even though the time variable in these problems has a discrete aspect, a variational inequality can be obtained by considering an underlying continuous-time structure. Depending on whether stopping is allowed at t = 0, the value function exhibits different properties across the optimal exercise boundary. Indeed, the value function is only 𝒞 0 across the optimal boundary when stopping is allowed at t = 0 and 𝒞 2 otherwise, both contradicting the usual 𝒞 1 smoothness that is necessary and sufficient for the application of the principle of smooth fit. Also discussed is an equivalent stochastic control formulation for these stopping problems. Finally, we derive the asymptotic behaviour of the value functions and optimal exercise boundaries as the intensity of the Poisson process goes to infinity or, roughly speaking, as the problems converge to the classical continuous-time optimal stopping problems.

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9

Crisan, D., and O. Obanubi. "Particle filters with random resampling times." Stochastic Processes and their Applications 122, no. 4 (2012): 1332–68. http://dx.doi.org/10.1016/j.spa.2011.12.012.

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10

Arbieto, Alexander, André Junqueira, and Regis Soares. "Hitting times for random dynamical systems." Dynamical Systems 28, no. 4 (2013): 484–500. http://dx.doi.org/10.1080/14689367.2013.819413.

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11

Kuz'ma, V. M. "Optimal times for measuring random oscillations." International Applied Mechanics 31, no. 9 (1995): 769–75. http://dx.doi.org/10.1007/bf00846865.

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12

Cieplak, M., and M. Muthukumar. "Relaxation times of a random copolymer." Macromolecules 18, no. 6 (1985): 1350–51. http://dx.doi.org/10.1021/ma00148a055.

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13

Dupuis, Paul, and Hui Wang. "Optimal stopping with random intervention times." Advances in Applied Probability 34, no. 1 (2002): 141–57. http://dx.doi.org/10.1239/aap/1019160954.

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We consider a class of optimal stopping problems where the ability to stop depends on an exogenous Poisson signal process - we can only stop at the Poisson jump times. Even though the time variable in these problems has a discrete aspect, a variational inequality can be obtained by considering an underlying continuous-time structure. Depending on whether stopping is allowed att= 0, the value function exhibits different properties across the optimal exercise boundary. Indeed, the value function is only𝒞0across the optimal boundary when stopping is allowed att= 0 and𝒞2otherwise, both contradicting the usual𝒞1smoothness that is necessary and sufficient for the application of the principle of smooth fit. Also discussed is an equivalent stochastic control formulation for these stopping problems. Finally, we derive the asymptotic behaviour of the value functions and optimal exercise boundaries as the intensity of the Poisson process goes to infinity or, roughly speaking, as the problems converge to the classical continuous-time optimal stopping problems.

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14

Denisov, Denis, and Vitali Wachtel. "Exit times for integrated random walks." Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 51, no. 1 (2015): 167–93. http://dx.doi.org/10.1214/13-aihp577.

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15

Beghin, Luisa, and Enzo Orsingher. "Population Processes Sampled at Random Times." Journal of Statistical Physics 163, no. 1 (2016): 1–21. http://dx.doi.org/10.1007/s10955-016-1475-2.

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16

Doney, R. A. "Last exit times for random walks." Stochastic Processes and their Applications 31, no. 2 (1989): 321–31. http://dx.doi.org/10.1016/0304-4149(89)90096-3.

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17

Dong, Congzao, and Alexander Iksanov. "Weak convergence of random processes with immigration at random times." Journal of Applied Probability 57, no. 1 (2020): 250–65. http://dx.doi.org/10.1017/jpr.2019.88.

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AbstractBy a random process with immigration at random times we mean a shot noise process with a random response function (response process) in which shots occur at arbitrary random times. Such random processes generalize random processes with immigration at the epochs of a renewal process which were introduced in Iksanov et al. (2017) and bear a strong resemblance to a random characteristic in general branching processes and the counting process in a fixed generation of a branching random walk generated by a general point process. We provide sufficient conditions which ensure weak convergence of finite-dimensional distributions of these processes to certain Gaussian processes. Our main result is specialised to several particular instances of random times and response processes.

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18

Cooper, Colin, Alan Frieze, and Tomasz Radzik. "The cover times of random walks on random uniform hypergraphs." Theoretical Computer Science 509 (October 2013): 51–69. http://dx.doi.org/10.1016/j.tcs.2013.01.020.

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19

Allaart, Pieter C. "Prophet Inequalities for I.I.D. Random Variables with Random Arrival Times." Sequential Analysis 26, no. 4 (2007): 403–13. http://dx.doi.org/10.1080/07474940701620857.

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20

Di Crescenzo, Antonio. "On random motions with velocities alternating at Erlang-distributed random times." Advances in Applied Probability 33, no. 03 (2001): 690–701. http://dx.doi.org/10.1017/s0001867800011071.

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We analyse a non-Markovian generalization of the telegrapher's random process. It consists of a stochastic process describing a motion on the real line characterized by two alternating velocities with opposite directions, where the random times separating consecutive reversals of direction perform an alternating renewal process. In the case of Erlang-distributed interrenewal times, explicit expressions of the transition densities are obtained in terms of a suitable two-index pseudo-Bessel function. Some results on the distribution of the maximum of the process are also disclosed.

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21

Zeitouni, Ofer, Nina Gantert, and Amir Dembo. "Large deviations for random walk in random environment with holding times." Annals of Probability 32, no. 1B (2004): 996–1029. http://dx.doi.org/10.1214/aop/1079021470.

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22

Mingzhi, Mao, and Li Zhimin. "Asymptotic behavior for random walk in random environment with holding times." Acta Mathematica Scientia 30, no. 5 (2010): 1696–708. http://dx.doi.org/10.1016/s0252-9602(10)60163-4.

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23

Di Crescenzo, Antonio. "On random motions with velocities alternating at Erlang-distributed random times." Advances in Applied Probability 33, no. 3 (2001): 690–701. http://dx.doi.org/10.1239/aap/1005091360.

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We analyse a non-Markovian generalization of the telegrapher's random process. It consists of a stochastic process describing a motion on the real line characterized by two alternating velocities with opposite directions, where the random times separating consecutive reversals of direction perform an alternating renewal process. In the case of Erlang-distributed interrenewal times, explicit expressions of the transition densities are obtained in terms of a suitable two-index pseudo-Bessel function. Some results on the distribution of the maximum of the process are also disclosed.

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24

Mailler, Cécile, Peter Mörters, and Anna Senkevich. "Competing growth processes with random growth rates and random birth times." Stochastic Processes and their Applications 135 (May 2021): 183–226. http://dx.doi.org/10.1016/j.spa.2021.02.003.

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25

Bergqvist, Göran, and Peter Forrester. "Rank probabilities for real random $N\times N \times 2$ tensors." Electronic Communications in Probability 16 (2011): 630–37. http://dx.doi.org/10.1214/ecp.v16-1655.

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26

Cidon, Israel, Roch Guréin, Asad Khamisy, and Moshe Sidi. "On Queues with Interarrival Times Proportional to Service Times." Probability in the Engineering and Informational Sciences 10, no. 1 (1996): 87–107. http://dx.doi.org/10.1017/s0269964800004198.

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We analyze a family of queueing systems where the interarrival time In+1 between customers n and n + 1 depends on the service time Bn of customer n. Specifically, we consider cases where the dependency between In+1 and Bn is a proportionality relation and Bn is an exponentially distributed random variable. Such dependencies arise in the context of packet-switched networks that use rate policing functions to regulate the amount of data that can arrive to a link within any given time interval. These controls result in significant dependencies between the amount of work brought in by customers/packets and the time between successive customers. The models developed in the paper and the associated solutions are, however, of independent interest and are potentially applicable to other environments.Several scenarios that consist of adding an independent random variable to the interarrival time, allowing the proportionality to be random and the combination of the two are considered. In all cases, we provide expressions for the Laplace-Stieltjes Transform of the waiting time of a customer in the system. Numerical results are provided and compared to those of an equivalent system without dependencies.

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27

Peköz, Erol, Adrian Röllin, and Nathan Ross. "Pólya urns with immigration at random times." Bernoulli 25, no. 1 (2019): 189–220. http://dx.doi.org/10.3150/17-bej983.

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28

Wang, Hui. "Some control problems with random intervention times." Advances in Applied Probability 33, no. 2 (2001): 404–22. http://dx.doi.org/10.1017/s0001867800010867.

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We consider the problem of optimally tracking a Brownian motion by a sequence of impulse controls, in such a way as to minimize the total expected cost that consists of a quadratic deviation cost and a proportional control cost. The main feature of our model is that the control can only be exerted at the arrival times of an exogenous uncontrolled Poisson process (signal). In other words, the set of possible intervention times are discrete, random and determined by the signal process (not by the decision maker). We discuss both the discounted problem and the ergodic problem, where explicit solutions can be found. We also derive the asymptotic behavior of the optimal control policies and the value functions as the intensity of the Poisson process goes to infinity, or roughly speaking, as the set of admissible controls goes from the discrete-time impulse control to the continuous-time bounded variation control.

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29

Liang, Gechun, and Wei Wei. "Optimal switching at Poisson random intervention times." Discrete and Continuous Dynamical Systems - Series B 21, no. 5 (2016): 1483–505. http://dx.doi.org/10.3934/dcdsb.2016008.

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30

Lacaze, Bernard. "Random propagation times for ultrasonics through polyethyilene." Ultrasonics 111 (March 2021): 106313. http://dx.doi.org/10.1016/j.ultras.2020.106313.

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31

Bshouty, Nader H., Lisa Higham, and Jolanta Warpechowska-Gruca. "Meeting times of random walks on graphs." Information Processing Letters 69, no. 5 (1999): 259–65. http://dx.doi.org/10.1016/s0020-0190(99)00017-4.

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32

Kenyon, Astrid S., and David P. Morton. "Stochastic Vehicle Routing with Random Travel Times." Transportation Science 37, no. 1 (2003): 69–82. http://dx.doi.org/10.1287/trsc.37.1.69.12820.

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33

Janson, Svante, and Yuval Peres. "Hitting Times for Random Walks with Restarts." SIAM Journal on Discrete Mathematics 26, no. 2 (2012): 537–47. http://dx.doi.org/10.1137/100796352.

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34

Kolomeisky, Anatoly B. "Continuous-time random walks at all times." Journal of Chemical Physics 131, no. 23 (2009): 234114. http://dx.doi.org/10.1063/1.3276704.

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35

Mannion, David. "Products of $2 \times 2$ Random Matrices." Annals of Applied Probability 3, no. 4 (1993): 1189–218. http://dx.doi.org/10.1214/aoap/1177005279.

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36

Ben-Hamou, Anna, Eyal Lubetzky, and Yuval Peres. "Comparing mixing times on sparse random graphs." Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 55, no. 2 (2019): 1116–30. http://dx.doi.org/10.1214/18-aihp911.

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37

Allan, Gut. "First passage times for perturbed random walks." Sequential Analysis 11, no. 2 (1992): 149–79. http://dx.doi.org/10.1080/07474949208836251.

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38

Boshuizen, frans. "Minimax stopping times for I.I.D. Random variables." Sequential Analysis 11, no. 4 (1992): 327–37. http://dx.doi.org/10.1080/07474949208836264.

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39

Liang, Gechun, and Haodong Sun. "Dynkin Games with Poisson Random Intervention Times." SIAM Journal on Control and Optimization 57, no. 4 (2019): 2962–91. http://dx.doi.org/10.1137/18m1175720.

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40

Wang, Hui. "Some control problems with random intervention times." Advances in Applied Probability 33, no. 2 (2001): 404–22. http://dx.doi.org/10.1239/aap/999188321.

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41

Christensen, Sören, Albrecht Irle, and Stephan Jürgens. "Optimal Multiple Stopping with Random Waiting Times." Sequential Analysis 32, no. 3 (2013): 297–318. http://dx.doi.org/10.1080/07474946.2013.803814.

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42

Rousseau, Jérôme, and Mike Todd. "Hitting Times and Periodicity in Random Dynamics." Journal of Statistical Physics 161, no. 1 (2015): 131–50. http://dx.doi.org/10.1007/s10955-015-1325-7.

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43

Konsowa, Mokhtar, Fahimah Al-Awadhi, and András Telcs. "Commute times of random walks on trees." Discrete Applied Mathematics 161, no. 7-8 (2013): 1014–21. http://dx.doi.org/10.1016/j.dam.2012.10.006.

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44

Sengupta, Arindam, and A. Goswami. "Moments of escape times of random walk." Proceedings - Mathematical Sciences 109, no. 4 (1999): 397–400. http://dx.doi.org/10.1007/bf02837999.

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45

Aldous, David, and Persi Diaconis. "Strong uniform times and finite random walks." Advances in Applied Mathematics 8, no. 1 (1987): 69–97. http://dx.doi.org/10.1016/0196-8858(87)90006-6.

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46

Barma, Mustansir, and Ramakrishna Ramaswamy. "Escape times in interacting biased random walks." Journal of Statistical Physics 43, no. 3-4 (1986): 561–70. http://dx.doi.org/10.1007/bf01020653.

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47

Ren, Jiagang, and Xicheng Zhang. "Regularity of local times of random fields." Journal of Functional Analysis 249, no. 1 (2007): 199–219. http://dx.doi.org/10.1016/j.jfa.2007.04.017.

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48

Goodin, D. S., and M. J. Aminoff. "The non-random variability of reaction times." Electroencephalography and Clinical Neurophysiology 95, no. 2 (1995): P26. http://dx.doi.org/10.1016/0013-4694(95)97959-5.

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49

Yumei, Hou, Liu Wenyuan, Zhang Qiang, and Wu Fengqing. "Production inventory system with random supply interruptions statue and random lead times." Acta Mathematica Scientia 31, no. 1 (2011): 117–33. http://dx.doi.org/10.1016/s0252-9602(11)60214-2.

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50

Li, Yuqiang. "Moderate Deviations for Stable Random Walks in Random Scenery." Journal of Applied Probability 49, no. 01 (2012): 280–94. http://dx.doi.org/10.1017/s0021900200008998.

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In this paper, a moderate deviation theorem for one-dimensional stable random walks in random scenery is proved. The proof relies on the analysis of maximum local times of stable random walks, and the comparison of moments between random walks in random scenery and self-intersection local times of the underlying random walks.

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