Littérature scientifique sur le sujet « Time-series analysis »

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Articles de revues sur le sujet "Time-series analysis"

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Zhuravka, Fedir, Hanna Filatova, Petr Šuleř, and Tomasz Wołowiec. "State debt assessment and forecasting: time series analysis." Investment Management and Financial Innovations 18, no. 1 (2021): 65–75. http://dx.doi.org/10.21511/imfi.18(1).2021.06.

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One of the pressing problems in the modern development of the world financial system is an excessive increase in state debt, which has many negative consequences for the financial system of any country. At the same time, special attention should be paid to developing an effective state debt management system based on its forecast values. The paper is aimed at determining the level of persistence and forecasting future values of state debt in the short term using time series analysis, i.e., an ARIMA model. The study covers the time series of Ukraine’s state debt data for the period from Decembe
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Lutsenko, V. V., N. N. Kucherov, and A. V. Gladkov. "Predicting traffic congestion based on time series analysis." Sovremennaya nauka i innovatsii, no. 2 (42) (2023): 50–58. http://dx.doi.org/10.37493/2307-910x.2023.2.5.

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Traffic congestion is a serious problem in many cities, resulting in lost time, increased air pollution, and reduced quality of life. In the past few years, time series models have been widely used to predict traffic flows and congestion. This study analyzes traffic data collected over several years and develops a predictive model based on time series analysis techniques. The model takes into account various factors that contribute to congestion, such as time of day, day of the week, and junction. The results show that the model effectively predicts traffic congestion with a high degree of acc
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Lutsenko, V. V., N. N. Kucherov, and A. V. Gladkov. "PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS." Sovremennaya nauka i innovatsii, no. 1 (41) (2023): 47–55. http://dx.doi.org/10.37493/2307-910x.2023.1.4.

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Traffic congestion is a serious problem in many cities, resulting in lost time, increased air pollution, and reduced quality of life. In the past few years, time series models have been widely used to predict traffic flows and congestion. This study analyzes traffic data collected over several years and develops a predictive model based on time series analysis techniques. The model takes into account various factors that contribute to congestion, such as time of day, day of the week, and junction. The results show that the model effectively predicts traffic congestion with a high degree of acc
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Bowerman, Bruce, and Jonathan D. Cryer. "Time Series Analysis." Technometrics 29, no. 2 (1987): 240. http://dx.doi.org/10.2307/1269781.

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Donatelli, Richard E., Ji-Ae Park, Spencer M. Mathews, and Shin-Jae Lee. "Time series analysis." American Journal of Orthodontics and Dentofacial Orthopedics 161, no. 4 (2022): 605–8. http://dx.doi.org/10.1016/j.ajodo.2021.07.013.

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Potscher, Benedikt M., and James D. Hamilton. "Time Series Analysis." Journal of the American Statistical Association 91, no. 433 (1996): 439. http://dx.doi.org/10.2307/2291435.

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Bakouch, Hassan S. "Time Series Analysis." Journal of the Royal Statistical Society: Series A (Statistics in Society) 172, no. 1 (2009): 283. http://dx.doi.org/10.1111/j.1467-985x.2008.00571_4.x.

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Subba Rao, T. "Time Series Analysis." Journal of Time Series Analysis 31, no. 2 (2010): 139. http://dx.doi.org/10.1111/j.1467-9892.2009.00641.x.

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Breitung, Jorg, and James D. Hamilton. "Time Series Analysis." Contemporary Sociology 24, no. 2 (1995): 271. http://dx.doi.org/10.2307/2076916.

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Taylor, Diana. "Time-Series Analysis." Western Journal of Nursing Research 12, no. 2 (1990): 254–61. http://dx.doi.org/10.1177/019394599001200210.

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Thèses sur le sujet "Time-series analysis"

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Pope, Kenneth James. "Time series analysis." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318445.

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Yin, Jiang Ling. "Financial time series analysis." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2492929.

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Gore, Christopher Mark. "A time series classifier." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2008. http://scholarsmine.mst.edu/thesis/pdf/Gore_09007dcc804e6461.pdf.

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Thesis (M.S.)--Missouri University of Science and Technology, 2008.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed April 29, 2008) Includes bibliographical references (p. 53-55).
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Lam, Vai Iam. "Time domain approach in time series analysis." Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1446633.

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Malan, Karien. "Stationary multivariate time series analysis." Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-06132008-173800.

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Huang, Naijing. "Essays in time series analysis." Thesis, Boston College, 2015. http://hdl.handle.net/2345/bc-ir:104627.

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Thesis advisor: Zhijie Xiao<br>I have three chapters in my dissertation. The first chapter is about the estimation and inference for DSGE model; the second chapter is about testing financial contagion among stock markets, and in the last chapter, I propose a new econometrics method to forecast inflation interval. This first chapter studies proper inference and asymptotically accurate structural break tests for parameters in Dynamic Stochastic General Equilibrium (DSGE) models in a maximum likelihood framework. Two empirically relevant issues may invalidate the conventional inference procedures
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Alagon, J. "Discriminant analysis for time series." Thesis, University of Oxford, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.375222.

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Warnes, Alexis. "Diagnostics in time series analysis." Thesis, Durham University, 1994. http://etheses.dur.ac.uk/5159/.

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The portmanteau diagnostic test for goodness of model fit is studied. It is found that the true variances of the estimated residual autocorrelation function are potentially deflated considerably below their asymptotic level, and exhibit high correlations with each other. This suggests a new portmanteau test, ignoring the first p + q residual autocorrelation terms and hence approximating the asymptotic chi-squared distribution more closely. Simulations show that this alternative portmanteau test produces greater accuracy in its estimated significance levels, especially in small samples. Theory
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Chan, Hon Tsang. "Discriminant analysis of time series." Thesis, University of Newcastle Upon Tyne, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315614.

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Fulcher, Benjamin D. "Highly comparative time-series analysis." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:642b65cf-4686-4709-9f9d-135e73cfe12e.

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In this thesis, a highly comparative framework for time-series analysis is developed. The approach draws on large, interdisciplinary collections of over 9000 time-series analysis methods, or operations, and over 30 000 time series, which we have assembled. Statistical learning methods were used to analyze structure in the set of operations applied to the time series, allowing us to relate different types of scientific methods to one another, and to investigate redundancy across them. An analogous process applied to the data allowed different types of time series to be linked based on their pro
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Livres sur le sujet "Time-series analysis"

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Madsen, Henrik. Time series analysis. Chapman & Hall/CRC, 2008.

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Ostrom, Charles. Time Series Analysis. SAGE Publications, Inc., 1990. http://dx.doi.org/10.4135/9781412986366.

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Tanaka, Katsuto. Time Series Analysis. John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119132165.

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Cryer, Jonathan D., and Kung-Sik Chan. Time Series Analysis. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-75959-3.

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Maurice, Kendall. Time series. 3rd ed. Edward Arnold, 1993.

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C, Harvey A., ed. Time series. E. Elgar, 1994.

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Shumway, Robert H. Applied statistical time series analysis. Prentice-Hall International, 1988.

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Hardin, Jay C. Introduction to time series analysis. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1986.

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Harvey, A. C. The econometric analysis of time series. 2nd ed. P. Allen, 1990.

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Harvey, A. C. The econometric analysis of time series. MIT Press, 1989.

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Chapitres de livres sur le sujet "Time-series analysis"

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Tay, Dennis. "Time series analysis." In Data Analytics for Discourse Analysis with Python. Routledge, 2024. http://dx.doi.org/10.4324/9781003360292-5.

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Brandt, Siegmund. "Time Series Analysis." In Data Analysis. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03762-2_13.

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Arkes, Jeremy. "Time-series models." In Regression Analysis, 2nd ed. Routledge, 2022. http://dx.doi.org/10.4324/9781003285007-10.

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Brandt, Siegmund. "Time Series Analysis." In Data Analysis. Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-1446-5_13.

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Myers, Sara A. "Time Series." In Nonlinear Analysis for Human Movement Variability. CRC Press, 2018. http://dx.doi.org/10.1201/9781315370651-2.

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Baltagi, Badi H. "Time-Series Analysis." In Solutions Manual for Econometrics. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03383-4_14.

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Baltagi, Badi H. "Time-Series Analysis." In Econometrics. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58714-6_14.

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Chatfield, Christopher. "Time-series analysis." In Problem Solving. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4899-3017-0_19.

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Trauth, Martin H. "Time-Series Analysis." In MATLAB® Recipes for Earth Sciences. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46244-7_5.

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Baltagi, Badi H. "Time-Series Analysis." In Springer Texts in Business and Economics. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54548-1_14.

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Actes de conférences sur le sujet "Time-series analysis"

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Afonin, Nikita V., and Elena A. Skorodumova. "Time Series Analysis for Cointegration." In 2025 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF). IEEE, 2025. https://doi.org/10.1109/weconf65186.2025.11017151.

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Listiani, Indira Aprilia, Massimo Zanetti, and Francesca Bovolo. "Time Series Directional Change Vector Analysis." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642170.

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Kurbalija, Vladimir, and Brankica Bratic. "Time series reconstruction analysis." In 2016 IEEE 8th International Conference on Intelligent Systems (IS). IEEE, 2016. http://dx.doi.org/10.1109/is.2016.7737400.

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KESLER, SB. "INTERPLAY BETWEEN TIME SERIES ANALYSIS AND SPATIAL SERIES ANALYSIS." In International Conference on Spectral Analysis and its Use in Underwater Acoustics 1982. Institute of Acoustics, 2024. http://dx.doi.org/10.25144/23105.

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Müller, Ursula U., Anton Schick, and Wolfgang Wefelmeyer. "Inference for Alternating Time Series." In Recent Advances in Stochastic Modeling and Data Analysis. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812709691_0069.

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Dvořák, Marek. "Time series convolution kernel estimation." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2017). Author(s), 2018. http://dx.doi.org/10.1063/1.5044115.

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Mei, Xu, and Huang Chao. "Financial time series difference analysis based on symbolic time series method." In 2011 International Conference on E-Business and E-Government (ICEE). IEEE, 2011. http://dx.doi.org/10.1109/icebeg.2011.5882598.

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TARQUIS, ANA M., ROSA M. BENAVENTE, ANTONIO ROMERO, JOSÉ L. GARCÍA, and PHILIPPE BAVEYE. "WIND VELOCITY TIME SERIES ANALYSIS." In Conference on Fractals 2002. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812777720_0040.

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Kawamae, Noriaki. "Time Series Analysis Using NOC." In the 25th International Conference Companion. ACM Press, 2016. http://dx.doi.org/10.1145/2872518.2889396.

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Muñoz-Diosdado, A. "Multifractal Analysis of Time Series." In MODELING OF COMPLEX SYSTEMS: Seventh Granada Lectures. AIP, 2003. http://dx.doi.org/10.1063/1.1571344.

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Rapports d'organisations sur le sujet "Time-series analysis"

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Anderson, Theodore W. Time Series Analysis and Multivariate Statistical Analysis. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada202273.

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Anderson, Theodore W. Time Series Analysis and Multivariate Statistical Analysis. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada161375.

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Lai, Eric, Daniel Moyer, Baichuan Yuan, et al. Topic Time Series Analysis of Microblogs. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada610278.

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Friedman, Avner, Jr Miller, and Willard. Radar/Sonar and Time Series Analysis. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada238496.

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Ricca, Bernard. Nonlinear Time Series Analysis (Part I). Instats Inc., 2024. https://doi.org/10.61700/3t1w239ur7tk61382.

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This intensive four-day workshop provides a comprehensive introduction to nonlinear time series analysis, focusing on state space reconstruction and identifying evidence of nonlinear dynamics, using the R software. Participants will develop skills to manipulate, visualize, and create nonlinear models of time series data, enhancing their research in any field that works with time series data.
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Lipsett, J. J., R. D. Noble, and D. D. S. Liu. Time series analysis of gamma densitometry signals. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/302665.

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Langdon, Chris. Analysis of Arabian Sea Oxygen Time Series. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada628003.

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Lewis, Peter A., and A. J. Lawrance. Reversed Residuals in Autoregressive Time Series Analysis. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada222711.

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Parzen, Emanuel. Stationary Time Series Analysis Using Information and Spectral Analysis. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada257279.

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Wheat, Jr., Robert M. Chaos in Electronic Circuits: Nonlinear Time Series Analysis. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/821547.

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