IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v71y2014icp934-954.html
   My bibliography  Save this article

Basic Singular Spectrum Analysis and forecasting with R

Author

Listed:
  • Golyandina, Nina
  • Korobeynikov, Anton

Abstract

Singular Spectrum Analysis (SSA) is a powerful tool of analysis and forecasting of time series. The main features of the Rssa package, which efficiently implements the SSA algorithms and methodology in R, are described. Analysis, forecasting and parameter estimation are demonstrated using case studies. These studies are supplemented with accompanying code fragments.

Suggested Citation

  • Golyandina, Nina & Korobeynikov, Anton, 2014. "Basic Singular Spectrum Analysis and forecasting with R," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 934-954.
    • Handle: RePEc:eee:csdana:v:71:y:2014:i:c:p:934-954
    DOI: 10.1016/j.csda.2013.04.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947313001394
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2013.04.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Golyandina, Nina & Pepelyshev, Andrey & Steland, Ansgar, 2012. "New approaches to nonparametric density estimation and selection of smoothing parameters," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2206-2218.
    2. Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
    3. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aman Mohammad Kalteh, 2016. "Improving Forecasting Accuracy of Streamflow Time Series Using Least Squares Support Vector Machine Coupled with Data-Preprocessing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 747-766, January.
    2. Huffaker, R. & Canavari, M. & Muñoz-Carpena, R., 2018. "Distinguishing between endogenous and exogenous price volatility in food security assessment: An empirical nonlinear dynamics approach," Agricultural Systems, Elsevier, vol. 160(C), pages 98-109.
    3. Yuyang Gao & Chao Qu & Kequan Zhang, 2016. "A Hybrid Method Based on Singular Spectrum Analysis, Firefly Algorithm, and BP Neural Network for Short-Term Wind Speed Forecasting," Energies, MDPI, vol. 9(10), pages 1-28, September.
    4. Borke, Lukas & Härdle, Wolfgang Karl, 2016. "Q3-D3-Lsa," SFB 649 Discussion Papers 2016-049, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Qing Pei & David D Zhang & Guodong Li & Harry F Lee, 2015. "Climate Change and the Macroeconomic Structure in Pre-Industrial Europe: New Evidence from Wavelet Analysis," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-17, June.
    6. Hossein Hassani & Mahdi Kalantari & Zara Ghodsi, 2019. "Evaluating the Performance of Multiple Imputation Methods for Handling Missing Values in Time Series Data: A Study Focused on East Africa, Soil-Carbonate-Stable Isotope Data," Stats, MDPI, vol. 2(4), pages 1-11, December.
    7. Golyandina, Nina & Korobeynikov, Anton & Shlemov, Alex & Usevich, Konstantin, 2015. "Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i02).
    8. Mahdi Kalantari & Hossein Hassani, 2019. "Automatic Grouping in Singular Spectrum Analysis," Forecasting, MDPI, vol. 1(1), pages 1-16, October.
    9. Yuriy Zhukovskiy & Aleksandra Buldysko & Ilia Revin, 2023. "Induction Motor Bearing Fault Diagnosis Based on Singular Value Decomposition of the Stator Current," Energies, MDPI, vol. 16(8), pages 1-23, April.
    10. Aman Kalteh, 2016. "Improving Forecasting Accuracy of Streamflow Time Series Using Least Squares Support Vector Machine Coupled with Data-Preprocessing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 747-766, January.
    11. Winita Sulandari & Yudho Yudhanto & Paulo Canas Rodrigues, 2022. "The Use of Singular Spectrum Analysis and K-Means Clustering-Based Bootstrap to Improve Multistep Ahead Load Forecasting," Energies, MDPI, vol. 15(16), pages 1-22, August.
    12. Kalantari, Mahdi, 2021. "Forecasting COVID-19 pandemic using optimal singular spectrum analysis," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    13. Pohl Philipp, 2017. "Valuation of a Company using Time Series Analysis," Journal of Business Valuation and Economic Loss Analysis, De Gruyter, vol. 12(1), pages 1-39, February.
    14. repec:hum:wpaper:sfb649dp2016-049 is not listed on IDEAS
    15. de Carvalho, Miguel & Martos, Gabriel, 2020. "Brexit: Tracking and disentangling the sentiment towards leaving the EU," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1128-1137.
    16. Pan, Rui & Liu, Tongshen & Huang, Wei & Wang, Yuxin & Yang, Duo & Chen, Jie, 2023. "State of health estimation for lithium-ion batteries based on two-stage features extraction and gradient boosting decision tree," Energy, Elsevier, vol. 285(C).
    17. Tang, Wenjin & Bu, Hui & Ji, Yuqiong & Li, Zhongfei, 2024. "Market uncertainty and information content in complex seasonality of prices," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    18. Telesca, Luciano & Laib, Mohamed & Guignard, Fabian & Mauree, Dasaraden & Kanevski, Mikhail, 2019. "Linearity versus non-linearity in high frequency multilevel wind time series measured in urban areas," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 234-244.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2015. "Forecasting the price of gold," Applied Economics, Taylor & Francis Journals, vol. 47(39), pages 4141-4152, August.
    2. Donya Rahmani & Saeed Heravi & Hossein Hassani & Mansi Ghodsi, 2016. "Forecasting time series with structural breaks with Singular Spectrum Analysis, using a general form of recurrent formula," Papers 1605.02188, arXiv.org.
    3. Jacob Dice & Mallick Hossain & David Rodziewicz, 2024. "Flood Risk Exposures and Mortgage-Backed Security Asset Performance and Risk Sharing," Research Working Paper RWP 24-05, Federal Reserve Bank of Kansas City.
    4. Malte Willmes & Katherine M Ransom & Levi S Lewis & Christian T Denney & Justin J G Glessner & James A Hobbs, 2018. "IsoFishR: An application for reproducible data reduction and analysis of strontium isotope ratios (87Sr/86Sr) obtained via laser-ablation MC-ICP-MS," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-15, September.
    5. Adriano Z. Zambom & Ronaldo Dias, 2013. "A Review of Kernel Density Estimation with Applications to Econometrics," International Econometric Review (IER), Econometric Research Association, vol. 5(1), pages 20-42, April.
    6. Massimo Albanese, 2022. "Community Enterprises: Snapshots from Italy," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 8, ejes_v8_i.
    7. M. Atikur Rahman Khan & D.S. Poskitt, 2014. "On The Theory and Practice of Singular Spectrum Analysis Forecasting," Monash Econometrics and Business Statistics Working Papers 3/14, Monash University, Department of Econometrics and Business Statistics.
    8. Razmi, Fatemeh & Azali, M. & Chin, Lee & Shah Habibullah, Muzafar, 2016. "The role of monetary transmission channels in transmitting oil price shocks to prices in ASEAN-4 countries during pre- and post-global financial crisis," Energy, Elsevier, vol. 101(C), pages 581-591.
    9. repec:rdg:wpaper:em-dp2013-04 is not listed on IDEAS
    10. Hossein Hassani & Abdol S. Soofi & Anatoly Zhigljavsky, 2013. "Predicting inflation dynamics with singular spectrum analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 743-760, June.
    11. Arouna, Aminou & Fatognon, Irene Akoko & Saito, Kazuki & Futakuchi, Koichi, 2021. "Moving toward rice self-sufficiency in sub-Saharan Africa by 2030: Lessons learned from 10 years of the Coalition for African Rice Development," World Development Perspectives, Elsevier, vol. 21(C).
    12. Nicholas John Tierney & Dianne Cook & Tania Prvan, 2020. "brolgar: An R package to BRowse Over Longitudinal Data Graphically and Analytically in R," Monash Econometrics and Business Statistics Working Papers 43/20, Monash University, Department of Econometrics and Business Statistics.
    13. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    14. Michael Berlemann & Julia Freese & Sven Knoth, 2020. "Dating the start of the US house price bubble: an application of statistical process control," Empirical Economics, Springer, vol. 58(5), pages 2287-2307, May.
    15. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    16. Huang, Xu & Hassani, Hossein & Ghodsi, Mansi & Mukherjee, Zinnia & Gupta, Rangan, 2017. "Do trend extraction approaches affect causality detection in climate change studies?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 604-624.
    17. Jiří Sedláček, 2013. "Using R in Finance [Využití R v oblasti financí]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2013(4), pages 145-163.
    18. Stübinger, Johannes & Endres, Sylvia, 2017. "Pairs trading with a mean-reverting jump-diffusion model on high-frequency data," FAU Discussion Papers in Economics 10/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    19. Judith M. Ament & Robin Freeman & Chris Carbone & Anna Vassall & Charlotte Watts, 2020. "An Empirical Analysis of Synergies and Tradeoffs between Sustainable Development Goals," Sustainability, MDPI, vol. 12(20), pages 1-12, October.
    20. Anota, Amélie & Savina, Marion & Bascoul-Mollevi, Caroline & Bonnetain, Franck, 2017. "QoLR: An R Package for the Longitudinal Analysis of Health-Related Quality of Life in Oncology," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i12).
    21. Ohana-Levi, Noa & Munitz, Sarel & Ben-Gal, Alon & Netzer, Yishai, 2020. "Evaluation of within-season grapevine evapotranspiration patterns and drivers using generalized additive models," Agricultural Water Management, Elsevier, vol. 228(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:71:y:2014:i:c:p:934-954. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.