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Thematische Bibliographien / Stochastic processes / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Stochastic processes“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 5. Juli 2025

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1

Csenki, A., and J. Medhi. "Stochastic Processes." Statistician 45, no. 3 (1996): 393. http://dx.doi.org/10.2307/2988486.

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2

Kedem, Benjamin, and J. Medhi. "Stochastic Processes." Technometrics 38, no. 1 (February 1996): 85. http://dx.doi.org/10.2307/1268920.

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3

PE and Jyotiprasad Medhi. "Stochastic Processes." Journal of the American Statistical Association 90, no. 430 (June 1995): 810. http://dx.doi.org/10.2307/2291116.

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4

MTW and Sheldon Ross. "Stochastic Processes." Journal of the American Statistical Association 91, no. 436 (December 1996): 1754. http://dx.doi.org/10.2307/2291619.

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5

Medhi, J. "Stochastic Processes." Biometrics 51, no. 1 (March 1995): 387. http://dx.doi.org/10.2307/2533368.

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6

PE and Emanuel Parzen. "Stochastic Processes." Journal of the American Statistical Association 95, no. 451 (September 2000): 1020. http://dx.doi.org/10.2307/2669508.

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7

Frey, Michael. "Stochastic Processes." Technometrics 35, no. 3 (August 1993): 329–30. http://dx.doi.org/10.1080/00401706.1993.10485336.

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8

Frey, Michael. "Stochastic Processes." Technometrics 39, no. 2 (May 1997): 230–31. http://dx.doi.org/10.1080/00401706.1997.10485094.

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9

Saunders, Ian W., and Sheldon M. Ross. "Stochastic Processes." Journal of the American Statistical Association 80, no. 389 (March 1985): 250. http://dx.doi.org/10.2307/2288101.

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10

Casas, J. M., M. Ladra, and U. A. Rozikov. "Markov processes of cubic stochastic matrices: Quadratic stochastic processes." Linear Algebra and its Applications 575 (August 2019): 273–98. http://dx.doi.org/10.1016/j.laa.2019.04.016.

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11

Urbanik, K. "Analytic stochastic processes." Studia Mathematica 89, no. 3 (1988): 261–80. http://dx.doi.org/10.4064/sm-89-3-261-280.

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12

Freeman, J. M., and R. G. Gallager. "Discrete Stochastic Processes." Journal of the Operational Research Society 48, no. 1 (January 1997): 103. http://dx.doi.org/10.2307/3009951.

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13

Lund, Robert B., Zdzislaw Brzezniak, and Tomasz Zastawniak. "Basic Stochastic Processes." Journal of the American Statistical Association 95, no. 451 (September 2000): 1019. http://dx.doi.org/10.2307/2669504.

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14

Hoffmann, Marc. "Stationary Stochastic Processes." CHANCE 26, no. 3 (September 2013): 56–57. http://dx.doi.org/10.1080/09332480.2013.845460.

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15

Dümbgen, Lutz. "Combinatorial stochastic processes." Stochastic Processes and their Applications 52, no. 1 (August 1994): 75–92. http://dx.doi.org/10.1016/0304-4149(94)90101-5.

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16

Gallager, R. G. "Discrete Stochastic Processes." Journal of the Operational Research Society 48, no. 1 (January 1997): 103. http://dx.doi.org/10.1057/palgrave.jors.2600329.

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17

Gallager, R. G. "Discrete Stochastic Processes." Journal of the Operational Research Society 48, no. 1 (1997): 103–0103. http://dx.doi.org/10.1038/sj.jors.2600329.

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18

Gudder, Stanley. "Quantum stochastic processes." Foundations of Physics 20, no. 11 (November 1990): 1345–63. http://dx.doi.org/10.1007/bf01883490.

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19

Dinculeanu, Nicolae. "Vector-valued stochastic processes. V. Optional and predictable variation of stochastic measures and stochastic processes." Proceedings of the American Mathematical Society 104, no. 2 (February 1, 1988): 625. http://dx.doi.org/10.1090/s0002-9939-1988-0962839-8.

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20

Nataliia, Oberemok, and Oberemok Ivan. "STOCHASTIC PROCESSES IN PROJECT MANAGEMENT." EUREKA: Social and Humanities, no. 6 (November 29, 2018): 3–9. https://doi.org/10.21303/2504-5571.2018.00799.

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Performance of planned activities not always leads to the achievement of planned results in innovation projects with a high degree of uncertainty. Management of such specific projects requires the usage of specific methods and processes. It is necessary to develop own stochastic process methods rather than use classical methods of deterministic management.  The main peculiarity of stochastic processes of projects consists in the inability to carry out more than one experiment. Implementation of a project is a stochastic process, which is carried out only once.  For the purposes of the research, stochastic project management is the process of organisation, planning and control over projects, in which the decisions and actions of managers are described by stochastic functions. If the project realisation is described by stochastic processes, the project management process is indeed described by stochastic processes.  This research suggests a project management approach based on the focus on the project product and project management as stochastic processes based on stochastic functions. It is demonstrated that stochastic function values, which underlie the stochastic processes, are formed by the intellectual instruments of those involved in the project and are developed on the basis of their knowledge and skills. The latter, in turn, are the result of studying and practical work on the project. Therefore, it is difficult to predict decisions and actions of managers and contractors, even if internal and external influences on them are specified. Then, any decisions or actions of such persons with regard to the external observer are described by stochastic functions.  The purpose of this study is to describe the processes of stochastic project management. The purpose of the study is the project management process. The subject of research is the methods of stochastic project management. Within the framework of the study, all groups of processes of stochastic control will be mathematically described and the conditions of their impact determined. The processes of stochastic project management are outlined and formally presented. These are the processes of project management organisation, the processes of project management support, processes of project content definition, processes of defining the resources, required for the project works, processes of project planning, processes of influence on contractors of actions (works).

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21

Metcalfe, A. V., and G. F. Lawler. "Introduction to Stochastic Processes." Statistician 45, no. 4 (1996): 533. http://dx.doi.org/10.2307/2988557.

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22

Bingham, Nick, and E. Cinlar. "Seminar on Stochastic Processes." Applied Statistics 42, no. 2 (1993): 408. http://dx.doi.org/10.2307/2986243.

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23

Applebaum, David, P. W. Jones, and P. Smith. "Stochastic Processes, an Introduction." Mathematical Gazette 86, no. 507 (November 2002): 567. http://dx.doi.org/10.2307/3621201.

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24

Kirmani, S. N. U. A., R. N. Bhattacharya, and E. C. Waymire. "Stochastic Processes with Applications." Technometrics 34, no. 1 (February 1992): 99. http://dx.doi.org/10.2307/1269558.

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25

Aurzada, Frank, Martin Kolb, Francoise Pène, and Vitali Wachtel. "Stochastic Processes under Constraints." Oberwolfach Reports 17, no. 4 (September 13, 2021): 1601–56. http://dx.doi.org/10.4171/owr/2020/32.

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26

Holubec, Viktor, Artem Ryabov, Sarah A. M. Loos, and Klaus Kroy. "Equilibrium stochastic delay processes." New Journal of Physics 24, no. 2 (February 1, 2022): 023021. http://dx.doi.org/10.1088/1367-2630/ac4b91.

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Abstract Stochastic processes with temporal delay play an important role in science and engineering whenever finite speeds of signal transmission and processing occur. However, an exact mathematical analysis of their dynamics and thermodynamics is available for linear models only. We introduce a class of stochastic delay processes with nonlinear time-local forces and linear time-delayed forces that obey fluctuation theorems and converge to a Boltzmann equilibrium at long times. From the point of view of control theory, such ‘equilibrium stochastic delay processes’ are stable and energetically passive, by construction. Computationally, they provide diverse exact constraints on general nonlinear stochastic delay problems and can, in various situations, serve as a starting point for their perturbative analysis. Physically, they admit an interpretation in terms of an underdamped Brownian particle that is either subjected to a time-local force in a non-Markovian thermal bath or to a delayed feedback force in a Markovian thermal bath. We illustrate these properties numerically for a setup familiar from feedback cooling and point out experimental implications.

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27

Robinson, P. M., and David Pollard. "Convergence of Stochastic Processes." Economica 52, no. 208 (November 1985): 529. http://dx.doi.org/10.2307/2553898.

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28

Barbour, A. D., and Sidney I. Resnick. "Adventures in Stochastic Processes." Journal of the American Statistical Association 88, no. 424 (December 1993): 1474. http://dx.doi.org/10.2307/2291307.

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29

PE and G. F. Lawler. "Introduction to Stochastic Processes." Journal of the American Statistical Association 90, no. 432 (December 1995): 1493. http://dx.doi.org/10.2307/2291555.

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30

Urbanik, K. "Analytic stochastic processes II." Studia Mathematica 97, no. 3 (1990): 253–65. http://dx.doi.org/10.4064/sm-97-3-253-265.

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31

Lawler, G. F. "Introduction to Stochastic Processes." Biometrics 53, no. 2 (June 1997): 783. http://dx.doi.org/10.2307/2533988.

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32

Shanmugam, Ramalingam. "Stochastic processes with applications." Journal of Statistical Computation and Simulation 83, no. 3 (March 2013): 597–98. http://dx.doi.org/10.1080/00949655.2012.654634.

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33

Freeman, Jim, and J. Medhi. "Stochastic Processes (Second Edition)." Journal of the Operational Research Society 47, no. 6 (June 1996): 836. http://dx.doi.org/10.2307/3010294.

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34

Mathar, Rudolf, Roy D. Yates, and David J. Goodman. "Probability and Stochastic Processes." Journal of the American Statistical Association 94, no. 448 (December 1999): 1387. http://dx.doi.org/10.2307/2669957.

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35

Veretennikov, Alexander. "Stochastic Processes and Models." Bulletin of the London Mathematical Society 39, no. 1 (January 16, 2007): 167–69. http://dx.doi.org/10.1112/blms/bdl020.

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36

Kailath, T., and H. V. Poor. "Detection of stochastic processes." IEEE Transactions on Information Theory 44, no. 6 (1998): 2230–31. http://dx.doi.org/10.1109/18.720538.

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37

Airila, M. I., and O. Dumbrajs. "Stochastic processes in gyrotrons." Nuclear Fusion 43, no. 11 (November 2003): 1446–53. http://dx.doi.org/10.1088/0029-5515/43/11/017.

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38

Lund, Robert. "Stochastic Processes. An Introduction." American Statistician 56, no. 4 (November 2002): 332–33. http://dx.doi.org/10.1198/tas.2002.s205.

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39

Fricks, John. "Stochastic Processes and Models." Journal of the American Statistical Association 102, no. 477 (March 2007): 381. http://dx.doi.org/10.1198/jasa.2007.s166.

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40

Bujorianu, Marius C., Manuela L. Bujorianu, and John Lygeros. "TRUE CONCURRENT STOCHASTIC PROCESSES." IFAC Proceedings Volumes 38, no. 1 (2005): 260–65. http://dx.doi.org/10.3182/20050703-6-cz-1902.00396.

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41

Bauwens, L. "Stochastic Conditional Intensity Processes." Journal of Financial Econometrics 4, no. 3 (May 17, 2006): 450–93. http://dx.doi.org/10.1093/jjfinec/nbj013.

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42

Guillas, Serge. "Doubly stochastic Hilbertian processes." Journal of Applied Probability 39, no. 3 (September 2002): 566–80. http://dx.doi.org/10.1239/jap/1034082128.

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In this paper, we consider a Hilbert-space-valued autoregressive stochastic sequence (Xn) with several regimes. We suppose that the underlying process (In) which drives the evolution of (Xn) is stationary. Under some dependence assumptions on (In), we prove the existence of a unique stationary solution, and with a symmetric compact autocorrelation operator, we can state a law of large numbers with rates and the consistency of the covariance estimator. An overall hypothesis states that the regimes where the autocorrelation operator's norm is greater than 1 should be rarely visited.

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43

Freeman, Jim. "Stochastic Processes (Second Edition)." Journal of the Operational Research Society 47, no. 6 (June 1996): 836–37. http://dx.doi.org/10.1057/jors.1996.106.

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44

Eleutério, Samuel, and R. Vilela Mendes. "Stochastic ground-state processes." Physical Review B 50, no. 8 (August 15, 1994): 5035–40. http://dx.doi.org/10.1103/physrevb.50.5035.

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45

Wendelberger, Joanne R. "Adventures in Stochastic Processes." Technometrics 35, no. 4 (November 1993): 461. http://dx.doi.org/10.1080/00401706.1993.10485374.

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46

Antoniou, I., and K. Gustafson. "Wavelets and stochastic processes." Mathematics and Computers in Simulation 49, no. 1-2 (July 1999): 81–104. http://dx.doi.org/10.1016/s0378-4754(99)00009-9.

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47

Hardin, Russell. "Ethics and Stochastic Processes." Social Philosophy and Policy 7, no. 1 (1989): 69–80. http://dx.doi.org/10.1017/s0265052500001023.

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There is some irony, and perhaps a bit of gallows humor, in opening a paper in this volume with the claim that “applied ethics” is a misnomer. Yet that claim is true in the following sense. What we need for most of the issues that have sparked the contemporary resurgence of moral and political theory is not the application of ethics as we know it, but the revamping of ethics to make it relevant to the issues we face. It is in our concern with major policy programs that ethics and political philosophy are most commonly rejoined to become a unified enquiry after a nearly complete separation through most of this century. Yet, ethical theories may be shaken to their foundations by our effort to apply them to policy problems. I do not propose to revamp ethics here, but only to show that much ethical theory cannot readily be applied to major policy problems.There are at least three important characteristics of major policy issues in general that may give traditional moral theories difficulties. First, such issues can generally be handled only by institutional intervention; they commonly cannot be resolved through uncoordinated individual action. Theories formulated at the individual level must therefore be recast to handle institutional actions and possibilities. Second, major policy issues typically have complicating strategic interactions between individuals at their bases. Third, they are inherently stochastic in the important sense that they affect large numbers with more or less determinable (or merely guessable) probabilities. C. H. Waddington calls such issues instances of “the problem of the ethics of stochastic processes.”

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48

Kern, Peter, and Lina Wedrich. "Dilatively semistable stochastic processes." Statistics & Probability Letters 99 (April 2015): 101–8. http://dx.doi.org/10.1016/j.spl.2015.01.008.

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49

Guillas, Serge. "Doubly stochastic Hilbertian processes." Journal of Applied Probability 39, no. 03 (September 2002): 566–80. http://dx.doi.org/10.1017/s002190020002180x.

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In this paper, we consider a Hilbert-space-valued autoregressive stochastic sequence (X n ) with several regimes. We suppose that the underlying process (I n ) which drives the evolution of (X n ) is stationary. Under some dependence assumptions on (I n ), we prove the existence of a unique stationary solution, and with a symmetric compact autocorrelation operator, we can state a law of large numbers with rates and the consistency of the covariance estimator. An overall hypothesis states that the regimes where the autocorrelation operator's norm is greater than 1 should be rarely visited.

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50

Singh, Pradyumna S., and Serge G. Lemay. "Stochastic Processes in Electrochemistry." Analytical Chemistry 88, no. 10 (May 5, 2016): 5017–27. http://dx.doi.org/10.1021/acs.analchem.6b00683.

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