Relevant bibliographies by topics / Time series

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Time series'

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

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Journal articles on the topic "Time series"

1

Cipra, Tomáš. "Asymmetric recursive methods for time series." Applications of Mathematics 39, no. 3 (1994): 203–14. http://dx.doi.org/10.21136/am.1994.134253.

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Ratinger, Tomáš. "Seasonal time series with missing observations." Applications of Mathematics 41, no. 1 (1996): 41–55. http://dx.doi.org/10.21136/am.1996.134312.

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CIUIU, Daniel. "STRICT STATIONARY TIME SERIES AND AUTOCOPULA." Review of the Air Force Academy 16, no. 2 (2018): 53–58. http://dx.doi.org/10.19062/1842-9238.2018.16.2.6.

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Sood, Parul, Pawan Patidar, and Piyush Piyush. "AI-Driven Crypto Time Series Forecasting." International Journal of Research Publication and Reviews 6, sp5 (2025): 217–23. https://doi.org/10.55248/gengpi.6.sp525.1929.

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Ray, W. D., Maurice Kendall, and J. K. Ord. "Time Series." Journal of the Royal Statistical Society. Series A (Statistics in Society) 157, no. 2 (1994): 308. http://dx.doi.org/10.2307/2983371.

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Booth, David E., Maurice Kendall, and J. Keith Ord. "Time Series." Technometrics 34, no. 1 (1992): 118. http://dx.doi.org/10.2307/1269585.

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KK, Maurice Kendall, and J. Keith Ord. "Time Series." Journal of the American Statistical Association 90, no. 432 (1995): 1492. http://dx.doi.org/10.2307/2291552.

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KK and Andrew Harvey. "Time Series." Journal of the American Statistical Association 90, no. 432 (1995): 1493. http://dx.doi.org/10.2307/2291556.

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Ziegel, Eric R. "Time Series." Technometrics 44, no. 4 (2002): 408. http://dx.doi.org/10.1198/tech.2002.s95.

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Holmes, William M. "Time Series." International Journal of Forecasting 7, no. 4 (1992): 532–33. http://dx.doi.org/10.1016/0169-2070(92)90037-a.

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Dissertations / Theses on the topic "Time series"

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Rajan, Jebu Jacob. "Time series classification." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339538.

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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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NETO, ANSELMO CHAVES. "BOOTSTRAP IN TIME SERIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1991. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8324@1.

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O bootstrap de B. Efron, que não poderia ser imaginado sem os computadores de hoje, pode resolver vários problemas livre da suposição de Gaussianidade para os dados. Este trabalho tem o objetivo de apresentar essa técnica computacionalmente intensiva no contexto de Séries temporais - Metodologia Box and Jenkins. Como se sabe essa Metodologia possui alguns resultados assintóticos. Então, na fase da identificação da estrutura do modelo, pode apresentar problemas em regiões do espaço paramétrico aqui determinadas,. O bootstrap é proposto como opção e um estudo de simulação, comparativo,
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AGUIAR, JOSE LUIZ DO NASCIMENTO DE. "TIME SERIES SYMILARITY MEASURES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=27789@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>Atualmente, uma tarefa muito importante na mineração de dados é compreender como extrair os dados mais informativos dentre um número muito grande de dados. Uma vez que todos os campos de conhecimento apresentam uma grande quantidade de dados que precisam ser reduzidas até as informações mais representativas, a abordagem das séries temporais é definitivamente um método muito forte para representar e extrair estas informações. No entanto nós pr
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Yin, Yong. "Outliers in Time Series /." Connect to resource, 1995. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1262638388.

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Rana, Md Mashud. "Energy time series prediction." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/11745.

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Reliable operations and economical utilization of power systems require electricity load forecasting at a wide range of forecasting horizons. The objective of this thesis is two-fold: developing accurate prediction models for electricity load forecasting, and quantifying the load forecasting uncertainty. At first, we consider the task of feature selection for electricity load forecasting. We propose a two-step approach - identifying a set of candidate features based on the data characteristics and then selecting a subset of them using four different methods. We evaluate the performance of th
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Grubb, Howard John. "Multivariate time series modelling." Thesis, University of Bath, 1990. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280803.

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Ahsan, Ramoza. "Time Series Data Analytics." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-dissertations/529.

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Given the ubiquity of time series data, and the exponential growth of databases, there has recently been an explosion of interest in time series data mining. Finding similar trends and patterns among time series data is critical for many applications ranging from financial planning, weather forecasting, stock analysis to policy making. With time series being high-dimensional objects, detection of similar trends especially at the granularity of subsequences or among time series of different lengths and temporal misalignments incurs prohibitively high computation costs. Finding trend
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Books on the topic "Time series"

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Kendall, Maurice G. Time series. 3rd ed. E. Arnold, 1990.

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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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Chan, Ngai Hang. Time Series. John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9781118032466.

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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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Deistler, Manfred, and Wolfgang Scherrer. Time Series Models. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13213-1.

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Maoz, Dan, Amiel Sternberg, and Elia M. Leibowitz, eds. Astronomical Time Series. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8941-3.

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Powell, Thomas M., and John H. Steele, eds. Ecological Time Series. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-6881-0.

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Powell, Thomas M., and John H. Steele, eds. Ecological Time Series. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1769-6.

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Book chapters on the topic "Time series"

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Marin, Jean-Michel, and Christian P. Robert. "Time Series." In Springer Texts in Statistics. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8687-9_7.

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Venables, W. N., and B. D. Ripley. "Time Series." In Modern Applied Statistics with S-Plus. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4899-2819-1_14.

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Manly, Bryan F. J. "Time series." In Randomization and Monte Carlo Methods in Biology. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2995-2_9.

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Kass, Robert E., Uri T. Eden, and Emery N. Brown. "Time Series." In Springer Series in Statistics. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-9602-1_18.

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Venables, W. N., and B. D. Ripley. "Time Series." In Statistics and Computing. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2719-7_15.

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Rouan, Daniel. "Time Series." In Encyclopedia of Astrobiology. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-11274-4_1593.

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Gooch, Jan W. "Time Series." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15403.

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Hull, Isaiah. "Time Series." In Machine Learning for Economics and Finance in TensorFlow 2. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6373-0_7.

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Mukhopadhyay, Sayan. "Time Series." In Advanced Data Analytics Using Python. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3450-1_6.

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Kenny, Peter. "Time Series." In Better Business Decisions from Data. Apress, 2014. http://dx.doi.org/10.1007/978-1-4842-0184-8_19.

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Conference papers on the topic "Time series"

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Stoilova, Krasimira, and Todor Stoilov. "Time Series Salaries Prediction." In 2024 XXXIII International Scientific Conference Electronics (ET). IEEE, 2024. http://dx.doi.org/10.1109/et63133.2024.10721542.

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Agrawal, Kunal, Sanjoy Baruah, Alan Burns, and Jinhao Zhao. "IDK Cascades for Time-Series Input Streams." In 2024 IEEE Real-Time Systems Symposium (RTSS). IEEE, 2024. https://doi.org/10.1109/rtss62706.2024.00017.

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Østergaard, Jan. "Directed Redundancy in Time Series." In 2024 IEEE International Symposium on Information Theory (ISIT). IEEE, 2024. http://dx.doi.org/10.1109/isit57864.2024.10619644.

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Combettes, Sylvain W., Charles Truong, and Laurent Oudre. "Symbolic Representation for Time Series." In 2024 32nd European Signal Processing Conference (EUSIPCO). IEEE, 2024. http://dx.doi.org/10.23919/eusipco63174.2024.10715214.

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Gunopulos, Dimitrios, and Gautam Das. "Time series similarity measures and time series indexing." In the 2001 ACM SIGMOD international conference. ACM Press, 2001. http://dx.doi.org/10.1145/375663.375808.

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de Carvalho, Osmar Abilio, Renato Fontes Guimaraes, Roberto Arnaldo Trancoso Gomes, and Nilton Correia da Silva. "Time series interpolation." In 2007 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/igarss.2007.4423211.

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Ye, Lexiang, and Eamonn Keogh. "Time series shapelets." In the 15th ACM SIGKDD international conference. ACM Press, 2009. http://dx.doi.org/10.1145/1557019.1557122.

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Francke, Marc. "Time Series Econometrics." In 25th Annual European Real Estate Society Conference. European Real Estate Society, 2016. http://dx.doi.org/10.15396/eres2016_380.

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Combes, Florian, Ricardo Fraiman, and Badih Ghattas. "Time Series Sampling." In ITISE 2022. MDPI, 2022. http://dx.doi.org/10.3390/engproc2022018032.

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Ye, Yufeng, Qichao He, Peng Zhang, Jie Xiao, and Zhao Li. "Multivariate Time Series Anomaly Detection with Fourier Time Series Transformer." In 2023 IEEE 12th International Conference on Cloud Networking (CloudNet). IEEE, 2023. http://dx.doi.org/10.1109/cloudnet59005.2023.10490086.

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Reports on the topic "Time series"

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Broemeling, Lyle. Changing Time Series. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada178030.

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Adler, Robert J., Raisa E. Feldman, and Colin Gallagher. Analysing Stable Time Series. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada336964.

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Ramos, Ernesto. Resampling Methods for Time Series. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada198942.

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Williamson, M. A. Benchmarking of energy time series. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6990845.

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Tichomirova, T. M., and A. G. Sukiasyan. Test bank «Time Series Models». Ailamazyan Program Systems Institute of Russian Academy of Sciences, 2023. http://dx.doi.org/10.12731/ofernio.2023.25215.

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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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Glynn, P. W., and D. L. Iglehart. The Theory of Standardized Time Series. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada158383.

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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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Jääskeläinen, Emmihenna. Construction of reliable albedo time series. Finnish Meteorological Institute, 2023. http://dx.doi.org/10.35614/isbn.9789523361782.

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A reliable satellite-based black-sky albedo time series is a crucial part of detecting changes in the climate. This thesis studies the solutions to several uncertainties impairing the quality of the black-sky albedo time series. These solutions include creating a long dynamic aerosol optical depth time series for enhancing the removal of atmospheric effects, a method to fill missing data to improve spatial and temporal coverage, and creating a function to correctly model the diurnal variation of melting snow albedo. Mathematical methods are the center pieces of the solutions found in this thes
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DeSmet, Chance, Michael Girard, Elizabeth Coda, and Yijing Watkins. Universal Fourier Attack for Time Series. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2338170.

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