IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v067i02.html

Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Package

Author

Listed:
  • Golyandina, Nina
  • Korobeynikov, Anton
  • Shlemov, Alex
  • Usevich, Konstantin

Abstract

Implementation of multivariate and 2D extensions of singular spectrum analysis (SSA) by means of the R package Rssa is considered. The extensions include MSSA for simultaneous analysis and forecasting of several time series and 2D-SSA for analysis of digital images. A new extension of 2D-SSA analysis called shaped 2D-SSA is introduced for analysis of images of arbitrary shape, not necessary rectangular. It is shown that implementation of shaped 2D-SSA can serve as a basis for implementation of MSSA and other generalizations. Efficient implementation of operations with Hankel and Hankel-block-Hankel matrices through the fast Fourier transform is suggested. Examples with code fragments in R, which explain the methodology and demonstrate the proper use of Rssa, are presented.

Suggested Citation

  • 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).
    • Handle: RePEc:jss:jstsof:v:067:i02
    DOI: http://hdl.handle.net/10.18637/jss.v067.i02
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v067i02/v67i02.pdf
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v067i02/Rssa_0.13-1.tar.gz
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v067i02/v67i02.R
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v067i02/v67i02-replication.zip
    Download Restriction: no
    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v067.i02?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
    ---><---

    References listed on IDEAS

    as
    1. Hossein Hassani & Saeed Heravi & Anatoly Zhigljavsky, 2013. "Forecasting UK Industrial Production with Multivariate Singular Spectrum Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 395-408, August.
    2. 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).
    3. Golyandina, Nina & Korobeynikov, Anton, 2014. "Basic Singular Spectrum Analysis and forecasting with R," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 934-954.
    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. Ilkka Launonen & Lasse Holmström, 2017. "Multivariate posterior singular spectrum analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 361-382, August.
    2. Paulo Canas Rodrigues & Olushina Olawale Awe & Jonatha Sousa Pimentel & Rahim Mahmoudvand, 2020. "Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks," Stats, MDPI, vol. 3(2), pages 1-21, June.
    3. Mahdi Kalantari & Hossein Hassani, 2019. "Automatic Grouping in Singular Spectrum Analysis," Forecasting, MDPI, vol. 1(1), pages 1-16, October.
    4. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
    5. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
    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. Kalantari, Mahdi, 2021. "Forecasting COVID-19 pandemic using optimal singular spectrum analysis," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    8. 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.
    9. 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. 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.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. Kun Zhang & Xing Huo & Kun Shao, 2023. "Temperature Time Series Prediction Model Based on Time Series Decomposition and Bi-LSTM Network," Mathematics, MDPI, vol. 11(9), pages 1-16, April.
    8. Percebois, Jacques & Pommeret, Stanislas, 2019. "Storage cost induced by a large substitution of nuclear by intermittent renewable energies: The French case," Energy Policy, Elsevier, vol. 135(C).
    9. Huang, Xu & Maçaira, Paula Medina & Hassani, Hossein & Cyrino Oliveira, Fernando Luiz & Dhesi, Gurjeet, 2019. "Hydrological natural inflow and climate variables: Time and frequency causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 480-495.
    10. Thelma Dede Baddoo & Zhijia Li & Yiqing Guan & Kenneth Rodolphe Chabi Boni & Isaac Kwesi Nooni, 2020. "Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions," IJERPH, MDPI, vol. 17(11), pages 1-26, June.
    11. Hansin Bilgili & Chwen Sheu, 2022. "A Bibliometric Review of the Mathematics Journal," Mathematics, MDPI, vol. 10(15), pages 1-17, July.
    12. Golyandina, Nina & Korobeynikov, Anton, 2014. "Basic Singular Spectrum Analysis and forecasting with R," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 934-954.
    13. Hassani, Hossein & Silva, Emmanuel Sirimal & Gupta, Rangan & Das, Sonali, 2018. "Predicting global temperature anomaly: A definitive investigation using an ensemble of twelve competing forecasting models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 121-139.
    14. Hassani, Hossein & Huang, Xu & Gupta, Rangan & Ghodsi, Mansi, 2016. "Does sunspot numbers cause global temperatures? A reconsideration using non-parametric causality tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 54-65.
    15. Andrea Saayman & Jacques de Klerk, 2019. "Forecasting tourist arrivals using multivariate singular spectrum analysis," Tourism Economics, , vol. 25(3), pages 330-354, May.
    16. Nikolaus Umlauf & Georg Mayr & Jakob Messner & Achim Zeileis, 2011. "Why Does It Always Rain on Me? A Spatio-Temporal Analysis of Precipitation in Austria," Working Papers 2011-25, Faculty of Economics and Statistics, Universität Innsbruck.
    17. Venencia, Cristian Darío & Agüero, José Luis & Salas Barboza, Ariela Griselda Judith & Cardón Pocoví, Julia Mercedes & Ortega Insaurralde, Carlos & Seghezzo, Lucas, 2025. "Complex relationships between large-scale land acquisitions, deforestation, and land zoning policies in agricultural frontiers," Land Use Policy, Elsevier, vol. 157(C).
    18. 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.
    19. Josu Arteche & Javier García‐Enríquez, 2022. "Singular spectrum analysis for value at risk in stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 3-16, January.
    20. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.

    More about this item

    Statistics

    Access and download statistics

    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:jss:jstsof:v:067:i02. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    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.