IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v39y2012i11p2313-2325.html
   My bibliography  Save this article

A wavelet-based time-varying autoregressive model for non-stationary and irregular time series

Author

Listed:
  • G. E. Salcedo
  • R. F. Porto
  • S. Y. Roa
  • F. R. Momo

Abstract

In this work we propose an autoregressive model with parameters varying in time applied to irregularly spaced non-stationary time series. We expand all the functional parameters in a wavelet basis and estimate the coefficients by least squares after truncation at a suitable resolution level. We also present some simulations in order to evaluate both the estimation method and the model behavior on finite samples. Applications to silicates and nitrites irregularly observed data are provided as well.

Suggested Citation

  • G. E. Salcedo & R. F. Porto & S. Y. Roa & F. R. Momo, 2012. "A wavelet-based time-varying autoregressive model for non-stationary and irregular time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2313-2325, June.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:11:p:2313-2325
    DOI: 10.1080/02664763.2012.702267
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2012.702267
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2012.702267?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. David J. Wright, 1986. "Forecasting Data Published at Irregular Time Intervals Using an Extension of Holt's Method," Management Science, INFORMS, vol. 32(4), pages 499-510, April.
    2. Sato, Joao R. & Morettin, Pedro A. & Arantes, Paula R. & Amaro Jr., Edson, 2007. "Wavelet based time-varying vector autoregressive modelling," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5847-5866, August.
    3. Cai, Zongwu & Fan, Jianqing & Yao, Qiwei, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
    4. Dahlhaus, R. & Neumann, M. & Von Sachs, R., 1997. "Nonlinear Wavelet Estimation of Time-Varying Autoregressive Processes," SFB 373 Discussion Papers 1997,34, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Tomáv{s} Cipra & José Trujillo & Asunción Robio, 1995. "Holt-Winters Method with Missing Observations," Management Science, INFORMS, vol. 41(1), pages 174-178, January.
    6. Iain M. Johnstone & Bernard W. Silverman, 1997. "Wavelet Threshold Estimators for Data with Correlated Noise," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(2), pages 319-351.
    Full references (including those not matched with items on IDEAS)

    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. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
    2. Shahbaz, Muhammad & Mahalik, Mantu Kumar & Shah, Syed Hasanat & Sato, João Ricardo, 2016. "Time-varying analysis of CO2 emissions, energy consumption, and economic growth nexus: Statistical experience in next 11 countries," Energy Policy, Elsevier, vol. 98(C), pages 33-48.
    3. Stephanos Papadamou & Nikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2019. "Spillover Effects of US QE and QE Tapering on African and Middle Eastern Stock Indices," JRFM, MDPI, vol. 12(2), pages 1-20, April.
    4. Cai, Zongwu & Ren, Yu & Yang, Bingduo, 2015. "A semiparametric conditional capital asset pricing model," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 117-126.
    5. Battaglia, Francesco, 2005. "Outliers in functional autoregressive time series," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 323-332, May.
    6. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    7. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sato, João Ricardo, 2015. "On the relationships between CO2 emissions, energy consumption and income: The importance of time variation," Energy Economics, Elsevier, vol. 49(C), pages 629-638.
    8. Xu, Meng & Li, Jialiang & Chen, Ying, 2017. "Varying coefficient functional autoregressive model with application to the U.S. treasuries," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 168-183.
    9. Herwartz, H. & Xu, F., 2010. "A functional coefficient model view of the Feldstein-Horioka puzzle," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 37-54, February.
    10. Delgado, Michael S. & McCloud, Nadine & Kumbhakar, Subal C., 2014. "A generalized empirical model of corruption, foreign direct investment, and growth," Journal of Macroeconomics, Elsevier, vol. 42(C), pages 298-316.
    11. Offer Lieberman & Peter C. B. Phillips, 2014. "Norming Rates And Limit Theory For Some Time-Varying Coefficient Autoregressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 592-623, November.
    12. Wishart, Justin Rory, 2011. "Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1871-1875.
    13. Wong, Heung & Ip, Wai-cheung & Zhang, Riquan, 2008. "Varying-coefficient single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1458-1476, January.
    14. E. Zacharias & T. Stengos, 2006. "Intertemporal pricing and price discrimination: a semiparametric hedonic analysis of the personal computer market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 371-386.
    15. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
    16. Cai, Zongwu, 2003. "Nonparametric estimation equations for time series data," Statistics & Probability Letters, Elsevier, vol. 62(4), pages 379-390, May.
    17. Wang, Qihua & Zhang, Riquan, 2009. "Statistical estimation in varying coefficient models with surrogate data and validation sampling," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2389-2405, November.
    18. Čížek, Pavel & Koo, Chao Hui, 2021. "Jump-preserving varying-coefficient models for nonlinear time series," Econometrics and Statistics, Elsevier, vol. 19(C), pages 58-96.
    19. Linton, Oliver & Xiao, Zhijie, 2019. "Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(2), pages 608-631.
    20. Hassani, Hossein & Yeganegi, Mohammad Reza & Gupta, Rangan, 2019. "Does inequality really matter in forecasting real housing returns of the United Kingdom?," International Economics, Elsevier, vol. 159(C), pages 18-25.

    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:taf:japsta:v:39:y:2012:i:11:p:2313-2325. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.