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Relevant bibliographies by topics / Continuous Time Random Walk

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Academic literature on the topic 'Continuous Time Random Walk'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Continuous Time Random Walk"

1

Lin, Fang, and Jing-Dong Bao. "Environment-dependent continuous time random walk." Chinese Physics B 20, no. 4 (2011): 040502. http://dx.doi.org/10.1088/1674-1056/20/4/040502.

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Wang, Wanli, Eli Barkai, and Stanislav Burov. "Large Deviations for Continuous Time Random Walks." Entropy 22, no. 6 (2020): 697. http://dx.doi.org/10.3390/e22060697.

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Recently observation of random walks in complex environments like the cell and other glassy systems revealed that the spreading of particles, at its tails, follows a spatial exponential decay instead of the canonical Gaussian. We use the widely applicable continuous time random walk model and obtain the large deviation description of the propagator. Under mild conditions that the microscopic jump lengths distribution is decaying exponentially or faster i.e., Lévy like power law distributed jump lengths are excluded, and that the distribution of the waiting times is analytical for short waiting

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Hwang, Kyo-Shin, and Wensheng Wang. "Chover-Type Laws of the Iterated Logarithm for Continuous Time Random Walks." Journal of Applied Mathematics 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/906373.

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A continuous time random walk is a random walk subordinated to a renewal process used in physics to model anomalous diffusion. In this paper, we establish Chover-type laws of the iterated logarithm for continuous time random walks with jumps and waiting times in the domains of attraction of stable laws.

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Meerschaert, Mark M., and Hans-Peter Scheffler. "Limit theorems for continuous-time random walks with infinite mean waiting times." Journal of Applied Probability 41, no. 3 (2004): 623–38. http://dx.doi.org/10.1239/jap/1091543414.

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A continuous-time random walk is a simple random walk subordinated to a renewal process used in physics to model anomalous diffusion. In this paper we show that, when the time between renewals has infinite mean, the scaling limit is an operator Lévy motion subordinated to the hitting time process of a classical stable subordinator. Density functions for the limit process solve a fractional Cauchy problem, the generalization of a fractional partial differential equation for Hamiltonian chaos. We also establish a functional limit theorem for random walks with jumps in the strict generalized doma

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Meerschaert, Mark M., and Hans-Peter Scheffler. "Limit theorems for continuous-time random walks with infinite mean waiting times." Journal of Applied Probability 41, no. 03 (2004): 623–38. http://dx.doi.org/10.1017/s002190020002043x.

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A continuous-time random walk is a simple random walk subordinated to a renewal process used in physics to model anomalous diffusion. In this paper we show that, when the time between renewals has infinite mean, the scaling limit is an operator Lévy motion subordinated to the hitting time process of a classical stable subordinator. Density functions for the limit process solve a fractional Cauchy problem, the generalization of a fractional partial differential equation for Hamiltonian chaos. We also establish a functional limit theorem for random walks with jumps in the strict generalized doma

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Alemany, P. A., R. Vogel, I. M. Sokolov, and A. Blumen. "A dumbbell's random walk in continuous time." Journal of Physics A: Mathematical and General 27, no. 23 (1994): 7733–38. http://dx.doi.org/10.1088/0305-4470/27/23/016.

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Sabhapandit, Sanjib. "Record statistics of continuous time random walk." EPL (Europhysics Letters) 94, no. 2 (2011): 20003. http://dx.doi.org/10.1209/0295-5075/94/20003.

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Becker-Kern, Peter, and Hans-Peter Scheffler. "On multiple-particle continuous-time random walks." Journal of Applied Mathematics 2004, no. 3 (2004): 213–33. http://dx.doi.org/10.1155/s1110757x04308065.

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Scaling limits of continuous-time random walks are used in physics to model anomalous diffusion in which particles spread at a different rate than the classical Brownian motion. In this paper, we characterize the scaling limit of the average of multiple particles, independently moving as a continuous-time random walk. The limit is taken by increasing the number of particles and scaling from microscopic to macroscopic view. We show that the limit is independent of the order of these limiting procedures and can also be taken simultaneously in both procedures. Whereas the scaling limit of a singl

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Lv, Longjin, Fu-Yao Ren, Jun Wang, and Jianbin Xiao. "Correlated continuous time random walk with time averaged waiting time." Physica A: Statistical Mechanics and its Applications 422 (March 2015): 101–6. http://dx.doi.org/10.1016/j.physa.2014.12.010.

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Zhang, Caiyun, Yuhang Hu, and Jian Liu. "Correlated continuous-time random walk with stochastic resetting." Journal of Statistical Mechanics: Theory and Experiment 2022, no. 9 (2022): 093205. http://dx.doi.org/10.1088/1742-5468/ac8c8e.

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Abstract It is known that the introduction of stochastic resetting in an uncorrelated random walk process can lead to the emergence of a stationary state, i.e. the diffusion evolves towards a saturation state, and a steady Laplace distribution is reached. In this paper, we turn to study the anomalous diffusion of the correlated continuous-time random walk considering stochastic resetting. Results reveal that it displays quite different diffusive behaviors from the uncorrelated one. For the weak correlation case, the stochastic resetting mechanism can slow down the diffusion. However, for the s

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Dissertations / Theses on the topic "Continuous Time Random Walk"

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Gubiec, Tomasz, and Ryszard Kutner. "Two-step memory within Continuous Time Random Walk." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-183316.

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Gubiec, Tomasz, and Ryszard Kutner. "Two-step memory within Continuous Time Random Walk." Diffusion fundamentals 20 (2013) 64, S. 1, 2013. https://ul.qucosa.de/id/qucosa%3A13643.

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Chang, Qiang. "Continuous-time random-walk simulation of surface kinetics." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1166592142.

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Li, Chao. "Option pricing with generalized continuous time random walk models." Thesis, Queen Mary, University of London, 2016. http://qmro.qmul.ac.uk/xmlui/handle/123456789/23202.

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The pricing of options is one of the key problems in mathematical finance. In recent years, pricing models that are based on the continuous time random walk (CTRW), an anomalous diffusive random walk model widely used in physics, have been introduced. In this thesis, we investigate the pricing of European call options with CTRW and generalized CTRW models within the Black-Scholes framework. Here, the non-Markovian character of the underlying pricing model is manifest in Black-Scholes PDEs with fractional time derivatives containing memory terms. The inclusion of non-zero interest rates leads t

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Niemann, Markus. "From Anomalous Deterministic Diffusion to the Continuous-Time Random Walk." Wuppertal Universitätsbibliothek Wuppertal, 2010. http://d-nb.info/1000127621/34.

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Niemann, Markus [Verfasser]. "From Anomalous Deterministic Diffusion to the Continuous-Time Random Walk / Markus Niemann." Wuppertal : Universitätsbibliothek Wuppertal, 2010. http://d-nb.info/1000127621/34.

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Helfferich, Julian [Verfasser], and Alexander [Akademischer Betreuer] Blumen. "Glass dynamics in the continuous-time random walk framework = Glasdynamik als Zufallsprozess." Freiburg : Universität, 2015. http://d-nb.info/1125885513/34.

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Allen, Andrew. "A Random Walk Version of Robbins' Problem." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404568/.

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Robbins' problem is an optimal stopping problem where one seeks to minimize the expected rank of their observations among all observations. We examine random walk analogs to Robbins' problem in both discrete and continuous time. In discrete time, we consider full information and relative ranks versions of this problem. For three step walks, we give the optimal stopping rule and the expected rank for both versions. We also give asymptotic upper bounds for the expected rank in discrete time. Finally, we give upper and lower bounds for the expected rank in continuous time, and we show that the ex

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Veretennikova, Maria. "Controlled continuous time random walks and their position dependent extensions." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/66990/.

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Continuous Time Random Walks (CTRWs) are used widely for modelling anomalous diffusion. This thesis is the first research which focuses on optimal control of CTRWs, their modifications and their position dependent extensions. We derive the equation which may be called a fractional Hamilton Jacobi Bellman equation (FHJB), as it is similar to the HJB equation for controlled Markov processes. We present our original analysis of the FHJB equation, firstly working with its simpler linear version and obtaining useful regularity properties, and secondly, deriving the mild form of the FHJB, exploring

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Денисов, Станіслав Іванович, Станислав Иванович Денисов, Stanislav Ivanovych Denysov, Юрій Сергійович Бистрик, Юрий Сергеевич Быстрик, and Yurii Serhiiovych Bystryk. "New asymptotic solutions of the unbiased continuous-time random walks." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/9941.

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Books on the topic "Continuous Time Random Walk"

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Jurlewicz, Agnieszka. Limit theorems for randomly coarse grained continuous-time random walks. Institute of Mathematics, Polish Academy of Sciences, 2005.

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Nicolas, Christian. Random walk. Architectural Association Students Union, 1998.

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Malkiel, Burton Gordon. A random walk down Wall Street: The time-tested strategy for successful investing. W.W. Norton, 2003.

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Malkiel, Burton Gordon. A random walk down Wall Street: The time-tested strategy for successful investing. W.W. Norton, 2003.

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Luger, Richard. Exact non-parametric tests for a random walk with unknown drift under conditional heteroscedasticity. Bank of Canada, 2001.

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Luger, Richard. Exact non-parametric tests for a random walk with unknown drift under conditional heteroscedasticity. Bank of Canada, 2001.

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7

Long, Richard. Dartmoor time: A continuous walk of 24 hours on Dartmoor... 55 miles, England Autumn 1995 = Dartmoor riverbed stones : river to river, stone to stone, a 2 1/2 day walk around the edge of Dartmoor. Spacex Gallery, 1996.

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Vanden-Eijnden, Eric, and Nawaf Bou-Rabee. Continuous-Time Random Walks for the Numerical Solution of Stochastic Differential Equations. American Mathematical Society, 2019.

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Zinn-Justin, Jean. From Random Walks to Random Matrices. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198787754.001.0001.

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Theoretical physics is a cornerstone of modern physics and provides a foundation for all modern quantitative science. It aims to describe all natural phenomena using mathematical theories and models and, in consequence, develops our understanding of the fundamental nature of the universe. This book offers an overview of major areas covering the recent developments in modern theoretical physics. Each chapter introduces a new key topic, and develops the discussion in a self-contained manner. At the same time, the selected topics have common themes running throughout the book, which connect the i

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Economic time series with random walk and other nonstationary components. Elsevier Science Publishers, 1988.

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Book chapters on the topic "Continuous Time Random Walk"

1

Jin, Bangti. "Continuous Time Random Walk." In Fractional Differential Equations. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76043-4_1.

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Schinazi, Rinaldo B. "Continuous Time Branching Random Walk." In Classical and Spatial Stochastic Processes. Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1582-0_6.

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Grigolini, Paolo. "The Continuous-Time Random Walk Versus the Generalized Master Equation." In Fractals, Diffusion, and Relaxation in Disordered Complex Systems. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471790265.ch5.

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Gorenflo, Rudolf, and Francesco Mainardi. "Fractional diffusion Processes: Probability Distributions and Continuous Time Random Walk." In Processes with Long-Range Correlations. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44832-2_8.

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Mülken, Oliver, and Alexander Blumen. "From Continuous-Time Random Walks to Continuous-Time Quantum Walks: Disordered Networks." In Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-017-8704-8_14.

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Lambiotte, Renaud. "Continuous-Time Random Walks and Temporal Networks." In Computational Social Sciences. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23495-9_12.

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Lambiotte, Renaud. "Continuous-Time Random Walks and Temporal Networks." In Computational Social Sciences. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30399-9_12.

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Méndez, Vicenç, Daniel Campos, and Frederic Bartumeus. "Anomalous Diffusion and Continuous-Time Random Walks." In Springer Series in Synergetics. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39010-4_4.

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Hadian Rasanan, Amir Hosein, Mohammad Mahdi Moayeri, Jamal Amani Rad, and Kourosh Parand. "From Continuous Time Random Walk Models to Human Decision-Making Modelling." In Mathematical Methods in Dynamical Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003328032-9.

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Meerschaert, Mark, and Hans Peter Scheffler. "Continuous time random walks and space-time fractional differential equations." In Basic Theory, edited by Anatoly Kochubei and Yuri Luchko. De Gruyter, 2019. http://dx.doi.org/10.1515/9783110571622-016.

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Conference papers on the topic "Continuous Time Random Walk"

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Capes, H., M. Christova, D. Boland, et al. "Modeling of Line Shapes using Continuous Time Random Walk Theory." In APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: Proceedings of the 2nd International Conference. AIP, 2010. http://dx.doi.org/10.1063/1.3526606.

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GORENFLO, R., F. MAINARDI, and A. VIVOLI. "SUBORDINATION IN FRACTIONAL DIFFUSION PROCESSES VIA CONTINUOUS TIME RANDOM WALK." In Proceedings of the 5th International ISAAC Congress. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789812835635_0043.

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Kang, Kang, Elsayed Abdelfatah, Maysam Pournik, Bor Jier Shiau, and Jeffrey Harwell. "Multiscale Modeling of Carbonate Acidizing Using Continuous Time Random Walk Approach." In SPE Kuwait Oil & Gas Show and Conference. Society of Petroleum Engineers, 2017. http://dx.doi.org/10.2118/187541-ms.

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Figueiredo, Daniel, Philippe Nain, Bruno Ribeiro, Edmundo de Souza e Silva, and Don Towsley. "Characterizing continuous time random walks on time varying graphs." In the 12th ACM SIGMETRICS/PERFORMANCE joint international conference. ACM Press, 2012. http://dx.doi.org/10.1145/2254756.2254794.

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Ribeiro, Bruno, Daniel Figueiredo, Edmundo de Souza e Silva, and Don Towsley. "Characterizing continuous-time random walks on dynamic networks." In the ACM SIGMETRICS joint international conference. ACM Press, 2011. http://dx.doi.org/10.1145/1993744.1993801.

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Capes, H., M. Christova, D. Boland, et al. "Revisiting the Stark Broadening by fluctuating electric fields using the Continuous Time Random Walk Theory." In 20TH INTERNATIONAL CONFERENCE ON SPECTRAL LINE SHAPES. AIP, 2010. http://dx.doi.org/10.1063/1.3517538.

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Wang, Yan. "Accelerating Stochastic Dynamics Simulation With Continuous-Time Quantum Walks." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59420.

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Stochastic diffusion is a general phenomenon observed in various national and engineering systems. It is typically modeled by either stochastic differential equation (SDE) or Fokker-Planck equation (FPE), which are equivalent approaches. Path integral is an accurate and effective method to solve FPEs. Yet, computational efficiency is the common challenge for path integral and other numerical methods, include time and space complexities. Previously, one-dimensional continuous-time quantum walk was used to simulate diffusion. By combining quantum diffusion and random diffusion, the new approach

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Paekivi, S., R. Mankin, and A. Rekker. "Interspike interval distribution for a continuous-time random walk model of neurons in the diffusion limit." In APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: 10th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences - AMiTaNS’18. Author(s), 2018. http://dx.doi.org/10.1063/1.5064927.

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EULE, S., and R. FRIEDRICH. "TOWARDS A PATH-INTEGRAL FORMULATION OF CONTINUOUS TIME RANDOM WALKS." In Proceedings of the 9th International Conference. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812837271_0087.

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Packwood, Daniel M. "Phase relaxation in slowly changing environments: Evaluation of the Kubo-Anderson model for a continuous-time random walk." In 4TH INTERNATIONAL SYMPOSIUM ON SLOW DYNAMICS IN COMPLEX SYSTEMS: Keep Going Tohoku. American Institute of Physics, 2013. http://dx.doi.org/10.1063/1.4794620.

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Reports on the topic "Continuous Time Random Walk"

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Lunsford, Kurt G., and Kenneth D. West. Random Walk Forecasts of Stationary Processes Have Low Bias. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202318.

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We study the use of a zero mean first difference model to forecast the level of a scalar time series that is stationary in levels. Let bias be the average value of a series of forecast errors. Then the bias of forecasts from a misspecified ARMA model for the first difference of the series will tend to be smaller in magnitude than the bias of forecasts from a correctly specified model for the level of the series. Formally, let P be the number of forecasts. Then the bias from the first difference model has expectation zero and a variance that is O(1/P²), while the variance of the bias from the l

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Ait-Sahalia, Yacine, and Per Mykland. The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions. National Bureau of Economic Research, 2002. http://dx.doi.org/10.3386/t0276.

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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM). Instats Inc., 2023. http://dx.doi.org/10.61700/kwigtxevhohxk469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta

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Pompeu, Gustavo, and José Luiz Rossi. Real/Dollar Exchange Rate Prediction Combining Machine Learning and Fundamental Models. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004491.

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The study of the predictability of exchange rates has been a very recurring theme on the economics literature for decades, and very often is not possible to beat a random walk prediction, particularly when trying to forecast short time periods. Although there are several studies about exchange rate forecasting in general, predictions of specifically Brazilian real (BRL) to United States dollar (USD) exchange rates are very hard to find in the literature. The objective of this work is to predict the specific BRL to USD exchange rates by applying machine learning models combined with fundamental

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Dormann, Christian. Introduction to Continuous Time Structural Equation Modeling (CTSEM) + 1 Free Seminar. Instats Inc., 2022. http://dx.doi.org/10.61700/am2g78fjl1gx5469.

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This seminar introduces the use of Continuous Time Structural Equation Modeling (CTSEM) to study phenomena over time in the social and health sciences. Day 1 topics include the required conceptual background, mathematical foundations, as well as examples to illustrate the concepts. On Day 2, the R package [b]ctsem [/b]is introduced, with hands-on coverage of topics including data preparation, model setup, parameter estimation, and interpretation of results. Day 3 topics include random intercept modelling (aka., within-person analysis), moderator analysis, and an outlook to Continuous Time Meta

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Lunsford, Kurt G., and Kenneth D. West. An Empirical Evaluation of Some Long-Horizon Macroeconomic Forecasts. Federal Reserve Bank of Cleveland, 2024. http://dx.doi.org/10.26509/frbc-wp-202420.

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We use long-run annual cross-country data for 10 macroeconomic variables to evaluate the long-horizon forecast distributions of six forecasting models. The variables we use range from ones having little serial correlation to ones having persistence consistent with unit roots. Our forecasting models include simple time series models and frequency domain models developed in Müller and Watson (2016). For plausibly stationary variables, an AR(1) model and a frequency domain model that does not require the user to take a stand on the order of integration appear reasonably well calibrated for foreca

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Derbentsev, V., A. Ganchuk, and Володимир Миколайович Соловйов. Cross correlations and multifractal properties of Ukraine stock market. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1117.

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Recently the statistical characterizations of ﬁnancial markets based on physics concepts and methods attract considerable attentions. The correlation matrix formalism and concept of multifractality are used to study temporal aspects of the Ukraine Stock Market evolution. Random matrix theory (RMT) is carried out using daily returns of 431 stocks extracted from database time series of prices the First Stock Trade System index (www.kinto.com) for the ten-year period 1997-2006. We ﬁnd that a majority of the eigenvalues of C fall within the RMT bounds for the eigenvalues of random correlation matr

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