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Books on the topic 'Time series'

Author: Grafiati

Published: 4 June 2021

Last updated: 22 February 2025

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1

Kendall, Maurice G. Time series. 3rd ed. Seven Oaks, Kent: E. Arnold, 1990.

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2

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

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3

C, Harvey A., ed. Time series. Aldershot, Hants, England: E. Elgar, 1994.

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4

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

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5

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

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6

Ostrom, Charles. Time Series Analysis. 2455 Teller Road, Thousand Oaks California 91320 United States of America: SAGE Publications, Inc., 1990. http://dx.doi.org/10.4135/9781412986366.

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7

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

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8

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

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9

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

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10

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

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11

Mills, Terence C. Time Series Econometrics. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137525338.

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12

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

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13

Levendis, John D. Time Series Econometrics. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98282-3.

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14

Neusser, Klaus. Time Series Econometrics. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32862-1.

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15

Cox, D. R., D. V. Hinkley, and O. E. Barndorff-Nielsen, eds. Time Series Models. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4899-2879-5.

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16

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

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17

Sharer, Elizabeth, and Hari Rajagopalan. Time Series Forecasting. 2455 Teller Road, Thousand Oaks California 91320 United States: SAGE Publications, Inc., 2023. http://dx.doi.org/10.4135/9781071910269.

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18

M, Powell T., and Steele John H. 1926-, eds. Ecological time series. New York: Chapman & Hall, 1995.

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19

Harvey, A. C. Time series models. 2nd ed. New York: Harvester Wheatsheaf, 1992.

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20

Harvey, A. C. Time series models. 2nd ed. New York: Harvester Wheatsheaf, 1993.

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21

Levendis, John D. Time Series Econometrics. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-37310-7.

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22

ill, Fairclough Chris, ed. Time: Knowabout series. London: F. Watts, 1988.

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23

Chan, Ngai Hang. Time Series. Wiley & Sons, Incorporated, John, 2011.

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24

McElroy, Tucker S., and Dimitris N. Politis. Time Series. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429109553.

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25

Prado, Raquel, and Mike West. Time Series. Chapman and Hall/CRC, 2010. http://dx.doi.org/10.1201/9781439882757.

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26

Time Series. Wiley & Sons Canada, Limited, John, 2004.

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27

Politis, Dimitris N., and Tucker McElroy. Time Series. Taylor & Francis Group, 2021.

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28

Time Series. Open University Worldwide, 2006.

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29

Chan, Jessie. Time Series. Wiley & Sons, Limited, John, 2020.

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30

Diggle, Peter, and Emanuele Giorgi. Time Series. 2nd ed. Oxford University PressOxford, 2024. https://doi.org/10.1093/oso/9780198714835.001.0001.

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Abstract This book is an introductory account of statistical methods for analysing time-series data, with a focus on the application of the methods to biomedical and population health research. In its simplest form, a time series is a single set of observations measured at equally spaced times. Extensions to this basic format that are particularly relevant in biomedical and population health settings include measurements at irregularly spaced times and independently replicated time series, also called longitudinal or repeated measurement data. The book starts by presenting a set of examples that we use in later chapters to show how the methods can be used to answer specific research questions. Later chapters cover simple descriptive methods for the display and exploratory analysis of time series data without any specific research objective; methods for discrete-time, continuous-time, and replicated time series; and spectral analysis and bivariate time series analysis. Three appendices summarize mathematical and statistical prerequisites. We have aimed to write a book that can be used either as a textbook for a masters-level course in biostatistics or as a manual for applied statisticians and epidemiologists.

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31

Time Series : Time Series: Theory and Methods. Springer, 2009.

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32

Time-series forecasting. Boca Raton: Chapman & Hall/CRC, 2001.

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33

Time series analysis. Hoboken: John Wiley & Sons, Inc., 2016.

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34

Palma, Wilfredo. Time Series Analysis. Wiley & Sons, Incorporated, John, 2016.

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35

Palma, Wilfredo. Time Series Analysis. Wiley & Sons, Incorporated, John, 2016.

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36

Palma, Wilfredo. Time Series Analysis. Wiley & Sons, Incorporated, John, 2016.

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37

Hannan, Edward James. Multiple Time Series. Wiley & Sons, Incorporated, John, 2009.

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38

Perron, Pierre. Time Series Econometrics. World Scientific Publishing Co Pte Ltd, 2019.

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39

Yao, Qiwei, and Jianqing Fan. Nonlinear Time Series. Springer, 2003.

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40

Chatfield, Chris. Time-Series Forecasting. Taylor & Francis Group, 2000.

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41

Chatfield, Chris. Time-Series Forecasting. Taylor & Francis Group, 2000.

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42

Chatfield, Chris. Time-Series Forecasting. Chapman & Hall/CRC, 2000.

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43

Chatfield, Christopher. Time-Series Forecasting. Taylor & Francis Group, 2001.

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44

Hamilton, James Douglas. Time Series Analysis. Princeton University Press, 2020.

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45

Gao, Jiti. Nonlinear Time Series. Taylor & Francis Group, 2019.

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46

Perron, Pierre. Time Series Econometrics. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/10930-vol1.

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47

Perron, Pierre. Time Series Econometrics. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/10930-vol2.

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48

Pevehouse, Jon, and Jason D. Brozek. Time‐Series Analysis. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0019.

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This article discusses time-series methods such as simple time-series regressions, ARIMA models, vector autoregression (VAR) models, and unit root and error correction models (ECM). It specifically presents a brief history of time-series analysis before moving to a review of the basic time-series model. It then describes the stationary models in univariate and multivariate analyses. The nonstationary models of each type are addressed. In addition, various issues regarding the analysis of time series including data aggregation and temporal stability are considered. Before concluding, the article briefly reports the time-series techniques in the context of panel data. In general, time-series analysis can help improve the understanding of the political world.

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49

Weigend, Andreas S. Time Series Prediction. Routledge, 2018. http://dx.doi.org/10.4324/9780429492648.

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50

Powell, Thomas M., and John H. Steele. Ecological Time Series. Springer, 1996.

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