Relevant bibliographies by topics / Ornstein-Uhlenbeck process

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Academic literature on the topic 'Ornstein-Uhlenbeck process'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Ornstein-Uhlenbeck process"

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Hidayat, Amam Taufiq, and Subanar Subanar. "PERSAMAAN DIFERENSIAL ORNSTEIN-UHLENBECK DALAM PERAMALAN HARGA SAHAM." MEDIA STATISTIKA 13, no. 1 (2020): 60–67. http://dx.doi.org/10.14710/medstat.13.1.60-67.

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Geometric Brownian motion is one of the most widely used stock price model. One of the assumptions that is filled with stock return volatility is constant. Gamma Ornstein-Uhlenbeck process a model to describe volatility in finance. Additionally, Gamma Ornstein-Uhlenbeck process driven by Background Driving Levy Process (BDLP) compound Poisson process and the marginal law of volatility follows a Gamma distribution. Barndorff-Nielsen and Shepard (BNS) Gamma Ornstein-Uhlenbeck model can to sample the process for the stock price with volatility follows Gamma Ornstein-Uhlenbeck process. Based on th
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Pedersen, Jan. "Periodic Ornstein-Uhlenbeck processes driven by Lévy processes." Journal of Applied Probability 39, no. 4 (2002): 748–63. http://dx.doi.org/10.1239/jap/1037816016.

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In this paper, the class of periodic Ornstein-Uhlenbeck processes is defined. It is shown that periodic Ornstein-Uhlenbeck processes are stationary Markov random fields and the class of stationary distributions is characterized. In particular, any self-decomposable distribution is the stationary distribution of some periodic Ornstein-Uhlenbeck process. As examples, gamma periodic Ornstein-Uhlenbeck processes and Gaussian periodic Ornstein-Uhlenbeck processes are considered.
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Pedersen, Jan. "Periodic Ornstein-Uhlenbeck processes driven by Lévy processes." Journal of Applied Probability 39, no. 04 (2002): 748–63. http://dx.doi.org/10.1017/s0021900200022014.

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In this paper, the class of periodic Ornstein-Uhlenbeck processes is defined. It is shown that periodic Ornstein-Uhlenbeck processes are stationary Markov random fields and the class of stationary distributions is characterized. In particular, any self-decomposable distribution is the stationary distribution of some periodic Ornstein-Uhlenbeck process. As examples, gamma periodic Ornstein-Uhlenbeck processes and Gaussian periodic Ornstein-Uhlenbeck processes are considered.
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Liu, Cheng-Shi. "Ornstein–Uhlenbeck process, Cauchy process, and Ornstein–Uhlenbeck–Cauchy process on a circle." Applied Mathematics Letters 26, no. 9 (2013): 957–62. http://dx.doi.org/10.1016/j.aml.2013.04.009.

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Debbasch, F., K. Mallick, and J. P. Rivet. "Relativistic Ornstein–Uhlenbeck Process." Journal of Statistical Physics 88, no. 3/4 (1997): 945–66. http://dx.doi.org/10.1023/b:joss.0000015180.16261.53.

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Borodin, A. N. "Hyperbolic Ornstein–Uhlenbeck Process." Journal of Mathematical Sciences 219, no. 5 (2016): 631–38. http://dx.doi.org/10.1007/s10958-016-3135-0.

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Garbaczewski, Piotr, and Robert Olkiewicz. "Ornstein–Uhlenbeck–Cauchy process." Journal of Mathematical Physics 41, no. 10 (2000): 6843. http://dx.doi.org/10.1063/1.1290054.

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Bishwal, Jaya P. N. "Minimum Contrast Estimation in Fractional Ornstein-Uhlenbeck Driven by Fractional Ornstein-Uhlenbeck Process." Asian Journal of Statistics and Applications 2, no. 1 (2025): 50–72. https://doi.org/10.47509/ajsa.2025.v02i01.04.

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We generalize fractional Ornstein-Uhlenbeck process whose driving term is another fractional Ornstein-Uhlenbeck process. The motivation is related to stochastic volatility model. We estimate the parameters of both processes by maximum likelihood method and minimum contrast method. We obtain strong consistency and asymptotic normality of the estimators as the time length of observation becomes large. KEYWORDS: Stochastic differential equation, fractional Brownian motion, fractional Ornstein-Uhlenbeck process, correlation, volatility, maximum likelihood estimator, minimum contrast estimator, Dur
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Ascione, Giacomo, Yuliya Mishura, and Enrica Pirozzi. "Time-changed fractional Ornstein-Uhlenbeck process." Fractional Calculus and Applied Analysis 23, no. 2 (2020): 450–83. http://dx.doi.org/10.1515/fca-2020-0022.

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AbstractWe define a time-changed fractional Ornstein-Uhlenbeck process by composing a fractional Ornstein-Uhlenbeck process with the inverse of a subordinator. Properties of the moments of such process are investigated and the existence of the density is shown. We also provide a generalized Fokker-Planck equation for the density of the process.
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Zang, Qing-Pei, and Li-Xin Zhang. "A general lower bound of parameter estimation for reflected Ornstein–Uhlenbeck processes." Journal of Applied Probability 53, no. 1 (2016): 22–32. http://dx.doi.org/10.1017/jpr.2015.5.

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AbstractA reflected Ornstein–Uhlenbeck process is a process that returns continuously and immediately to the interior of the state space when it attains a certain boundary. It is an extended model of the traditional Ornstein–Uhlenbeck process being extensively used in finance as a one-factor short-term interest rate model. Under some mild conditions, this paper is devoted to the study of the analogue of the Cramer–Rao lower bound of a general class of parameter estimation of the unknown parameter in reflected Ornstein–Uhlenbeck processes.
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Dissertations / Theses on the topic "Ornstein-Uhlenbeck process"

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Zhou, Sen Lin. "Geometric Asian option: Geometric Ornstein-Uhlenbeck process." Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/22062.

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Asian options, also known as average value options, are exotic options whose payoffs are dependent on the average prices of the underlying assets over the life of the options. The Asian options are very popular among the market participants when dealing with thinly traded commodities because the average property of the Asian options makes it very difficult to manipulate the payoffs of the options. Another reason for the popularity of Asian options is that they are cheaper than the corresponding portfolio of standard options to hedge the same exposure. The pricing of Asian options has been the
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Abdelrazeq, Ibrahim. "Statistical Inference for Lévy-Driven Ornstein-Uhlenbeck Processes." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31551.

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When an Ornstein-Uhlenbeck (or CAR(1)) process is observed at discrete times 0, h, 2h,··· [T/h]h, the unobserved driving process can be approximated from the ob- served process. Approximated increments of the driving process are used to test the assumption that the process is L\'evy-driven. Asymptotic behavior of the test statis- tic at high sampling frequencies is developed assuming that the model parameters are known. The behavior of the test statistics using an estimated parameter is also studied. If it can be concluded that the driving process is L\'evy, the empirical process of the approx
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Krämer, Romy, and Matthias Richter. "A Generalized Bivariate Ornstein-Uhlenbeck Model for Financial Assets." Universitätsbibliothek Chemnitz, 2008. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200800572.

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In this paper, we study mathematical properties of a generalized bivariate Ornstein-Uhlenbeck model for financial assets. Originally introduced by Lo and Wang, this model possesses a stochastic drift term which influences the statistical properties of the asset in the real (observable) world. Furthermore, we generali- ze the model with respect to a time-dependent (but still non-random) volatility function. Although it is well-known, that drift terms - under weak regularity conditions - do not affect the behaviour of the asset in the risk-neutral world and consequently the Black-Scholes option
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Erich, Roger Alan. "Regression Modeling of Time to Event Data Using the Ornstein-Uhlenbeck Process." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1342796812.

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Morlanes, José Igor. "Some Extensions of Fractional Ornstein-Uhlenbeck Model : Arbitrage and Other Applications." Doctoral thesis, Stockholms universitet, Statistiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-147437.

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This doctoral thesis endeavors to extend probability and statistical models using stochastic differential equations. The described models capture essential features from data that are not explained by classical diffusion models driven by Brownian motion. New results obtained by the author are presented in five articles. These are divided into two parts. The first part involves three articles on statistical inference and simulation of a family of processes related to fractional Brownian motion and Ornstein-Uhlenbeck process, the so-called fractional Ornstein-Uhlenbeck process of the second kind
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Deng, Yingjun. "Degradation modeling based on a time-dependent Ornstein-Uhlenbeck process and prognosis of system failures." Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0004/document.

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Cette thèse est consacrée à la description, la prédiction et la prévention des défaillances de systèmes. Elle se compose de quatre parties relatives à la modélisation stochastique de dégradation, au pronostic de défaillance du système, à l'estimation du niveau de défaillance et à l'optimisation de maintenance.Le processus d'Ornstein-Uhlenbeck (OU) dépendant du temps est introduit dans un objectif de modélisation des dégradations. Sur la base de ce processus, le premier instant de passage d’un niveau de défaillance prédéfini est considéré comme l’instant de défaillance du système considéré. Dif
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Jiang, Liqiu. "THE SIMULATION AND APPROXIMATION OF THE FIRST PASSAGE TIME OF THE ORNSTEIN--UHLENBECK PROCESS OF NEURON." NCSU, 2002. http://www.lib.ncsu.edu/theses/available/etd-04232002-224527/.

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Neurons communicate with each other via sequences of action potentials. The purpose of this study is to approximate the interval between action potentials which is also called the First Passage Time (FPT), the first time the membrane voltage passes a threshold. The subthreshold depolarization of a neuron receiving a multitude of random synaptic inputs has often been modelled as the Ornstein--Uhlenbeck (OU) process. This model provides an analytically tractable formalism of neuronal membrane voltage mean and variance in terms of a neuron's membrane time constant and the mean of input voltage. S
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Ющенко, Ольга Володимирівна, Ольга Владимировна Ющенко, Olha Volodymyrivna Yushchenko, Анна Юріївна Бадалян, Анна Юрьевна Бадалян, and Anna Yuriivna Badalian. "The Investigation of the External Influence on the Motion Regimes of Nanoparticles." Thesis, Sumy State University, 2012. http://essuir.sumdu.edu.ua/handle/123456789/34961.

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On the basis of self-consistent Lorenz system, taking into account the dispersion of the characteristic time of the average velocity variation the motion regimes of nanoparticles were investigated within the rigid mechanism of the self-organization. The influence of the environment was taken into account by means of a stochastic source in the equation describing the evolution of the control parameter. As a result, the Fokker-Planck equation has been obtained and has been solved in the steady state, the phase diagram of the system and the dependence of the average velocity of nanoparticles
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Aquino, Juan Carlos, and Gabriel Rodríguez. "Understanding the Functional Central Limit Theorems with Some Applications to Unit Root Testing with Structural Change." Economía, 2013. http://repositorio.pucp.edu.pe/index/handle/123456789/117824.

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The application of different unit root statistics is by now a standard practice in empirical work. Even when it is a practical issue, these statistics have complex nonstandard distributions depending on functionals of certain stochastic processes, and their derivations represent a barrier even for many theoretical econometricians. These derivations are based on rigorous and fundamental statistical tools which are not (very) well known by standard econometricians. This paper aims to fill this gap by explaining in a simple way one of these fundamental tools: namely, the Functional Central Limit
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Gay, Laura. "Processus d'Ornstein-Uhlenbeck et son supremum : quelques résultats théoriques et application au risque climatique." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEC025/document.

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Prévoir et estimer le risque de canicule est un enjeu politique majeur. Évaluer la probabilité d'apparition des canicules et leurs sévérités serait possible en connaissant la température en temps continu. Cependant, les extrêmes journaliers (maxima et minima) sont parfois les seules données disponibles. Pour modéliser la dynamique des températures, il est courant d'utiliser un processus d'Ornstein-Uhlenbeck. Une estimation des paramètres de ce processus n'utilisant que les suprema journaliers observés est proposée. Cette nouvelle approche se base sur une minimisation des moindres carrés faisan
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Books on the topic "Ornstein-Uhlenbeck process"

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Koski, Timo. Some metric order of entropy-properties of an infinite-dimensional Ornstein-Uhlenbeck process. Åbo akademi, 1985.

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Østerbø, Olav. Mathematical modelling and analysis of communication networks: Transient characteristics of traffic processes and models for end-to-end delay and delay-jitter. NTNU, 2003.

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Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications. World Scientific Publishing Co Pte Ltd, 2015.

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Book chapters on the topic "Ornstein-Uhlenbeck process"

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Borodin, Andrei N., and Paavo Salminen. "Ornstein-Uhlenbeck Process." In Handbook of Brownian Motion — Facts and Formulae. Birkhäuser Basel, 1996. http://dx.doi.org/10.1007/978-3-0348-7652-0_13.

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Borodin, Andrei N., and Paavo Salminen. "7. Ornstein–Uhlenbeck Process." In Probability and Its Applications. Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8163-0_14.

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Borodin, Andrei N., and Paavo Salminen. "8. Radial Ornstein–Uhlenbeck Process." In Probability and Its Applications. Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8163-0_15.

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Poczynek, Paula, Piotr Kruczek, and Agnieszka Wyłomańska. "Ornstein-Uhlenbeck Process Delayed by Gamma Subordinator." In Applied Condition Monitoring. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22529-2_8.

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Komorowski, Tomasz, Claudio Landim, and Stefano Olla. "Ornstein–Uhlenbeck Process with a Random Potential." In Grundlehren der mathematischen Wissenschaften. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29880-6_13.

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Helias, Moritz, and David Dahmen. "Ornstein–Uhlenbeck Process: The Free Gaussian Theory." In Statistical Field Theory for Neural Networks. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46444-8_8.

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Bishwal, Jaya P. N. "Parameter Estimation in Student Ornstein–Uhlenbeck Process." In Parameter Estimation in Stochastic Volatility Models. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-03861-7_10.

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Kubo, Izumi. "Non-isotropic Ornstein-Uhlenbeck Process and White Noise Analysis." In Stochastic Differential and Difference Equations. Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-1980-4_14.

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Lindstrøm, Tom. "Anderson’s Brownian motion and the Infinite Dimensional Ornstein-Uhlenbeck Process." In Advances in Analysis, Probability and Mathematical Physics. Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8451-7_16.

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Bishwal, Jaya P. N. "Berry–Esseen–Stein–Malliavin Theory for Fractional Ornstein–Uhlenbeck Process." In Parameter Estimation in Stochastic Volatility Models. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-03861-7_13.

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Conference papers on the topic "Ornstein-Uhlenbeck process"

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Zhang, Zhouhe, Haochen Hua, Xingying Chen, et al. "Spot Market Electricity Price Forecast via the Combination of Transformer and Ornstein-Uhlenbeck Process." In 2025 21st International Conference on the European Energy Market (EEM). IEEE, 2025. https://doi.org/10.1109/eem64765.2025.11050153.

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Perninge, Magnus, Mikael Amelin, and Valerijs Knazkins. "Load modeling using the Ornstein-Uhlenbeck process." In 2008 IEEE 2nd International Power and Energy Conference (PECon). IEEE, 2008. http://dx.doi.org/10.1109/pecon.2008.4762586.

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Coraluppi, Stefano, Craig Carthel, Jordan LeNoach, and Brandon Bale. "The Ornstein-Uhlenbeck Process in Multi-Target Tracking." In 2021 IEEE Aerospace Conference. IEEE, 2021. http://dx.doi.org/10.1109/aero50100.2021.9438389.

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Nauta, Johannes, Yara Khaluf, and Pieter Simoens. "Using the Ornstein-Uhlenbeck Process for Random Exploration." In 4th International Conference on Complexity, Future Information Systems and Risk. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007724500590066.

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Maben Rabi. "Efficient Sampling for Keeping Track of an Ornstein-Uhlenbeck Process." In 2006 14th Mediterranean Conference on Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/med.2006.235702.

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Rabi, Maben, John S. Baras, and George V. Moustakides. "Efficient Sampling for Keeping Track of an Ornstein-Uhlenbeck Process." In 2006 14th Mediterranean Conference on Control and Automation. IEEE, 2006. http://dx.doi.org/10.1109/med.2006.328849.

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Ghusinga, Khem Raj, Vaibhav Srivastava, and Abhyudai Singh. "Driving an Ornstein-Uhlenbeck Process to Desired First-Passage Time Statistics." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8795862.

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Rosenlind, Johanna, Fredrik Edstrom, Patrik Hilber, and Lennart Soder. "Modeling impact of cold load pickup on transformer aging using Ornstein-Uhlenbeck process." In 2013 IEEE Power & Energy Society General Meeting. IEEE, 2013. http://dx.doi.org/10.1109/pesmg.2013.6672841.

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Roberts, Ciaran, Emma M. Stewart, and Federico Milano. "Validation of the Ornstein-Uhlenbeck process for load modeling based on µPMU measurements." In 2016 Power Systems Computation Conference (PSCC). IEEE, 2016. http://dx.doi.org/10.1109/pscc.2016.7540898.

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Hadzagic, Melita, Maxime Isabelle, and Nathan Kashyap. "Hard and Soft Data Fusion for Maritime Traffic Monitoring Using the Integrated Ornstein-Uhlenbeck Process." In 2020 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA). IEEE, 2020. http://dx.doi.org/10.1109/cogsima49017.2020.9216117.

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Reports on the topic "Ornstein-Uhlenbeck process"

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Dankel, Jr, and Thad. On the Distribution of the Integrated Square of the Ornstein-Uhlenbeck Process. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada207253.

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