IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v26y2011i1p77-93.html
   My bibliography  Save this article

Detecting and modeling nonlinearity in the gas furnace data

Author

Listed:
  • Houston Stokes
  • Melvin Hinich

Abstract

No abstract is available for this item.

Suggested Citation

  • Houston Stokes & Melvin Hinich, 2011. "Detecting and modeling nonlinearity in the gas furnace data," Computational Statistics, Springer, vol. 26(1), pages 77-93, March.
    • Handle: RePEc:spr:compst:v:26:y:2011:i:1:p:77-93
    DOI: 10.1007/s00180-010-0211-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00180-010-0211-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00180-010-0211-7?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. Hinich, Melvin J & Patterson, Douglas M, 1985. "Evidence of Nonlinearity in Daily Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(1), pages 69-77, January.
    2. Richard A. Ashley & Douglas M. Patterson & Melvin J. Hinich, 1986. "A Diagnostic Test For Nonlinear Serial Dependence In Time Series Fitting Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 165-178, May.
    3. Hinich Melvin J & Mendes Eduardo M & Stone Lewi, 2005. "Detecting Nonlinearity in Time Series: Surrogate and Bootstrap Approaches," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-15, December.
    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. Nesmith Travis D & Jones Barry E, 2008. "Linear Cointegration of Nonlinear Time Series with an Application to Interest Rate Dynamics," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-18, March.
    2. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    3. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, June.
    4. T Tang, 2009. "Testing for Non-linearity in the Balancing Item of Balance of Payments Accounts: The Case of 20 Industrial Countries," Economic Issues Journal Articles, Economic Issues, vol. 14(2), pages 107-124, September.
    5. Lim, Kian-Ping & Brooks, Robert D. & Hinich, Melvin J., 2008. "Nonlinear serial dependence and the weak-form efficiency of Asian emerging stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 527-544, December.
    6. Teles, Paulo & Wei, William W. S., 2000. "The effects of temporal aggregation on tests of linearity of a time series," Computational Statistics & Data Analysis, Elsevier, vol. 34(1), pages 91-103, July.
    7. Phillip Wild & John Foster, 2012. "On testing for non-linear and time irreversible probabilistic structure in high frequency ASX financial time series data," Discussion Papers Series 466, School of Economics, University of Queensland, Australia.
    8. Kian-Ping Lim & M. Azali & M.S. Habibullah & Venus Khim-Sen Liew, 2003. "Are Non-Linear Dynamics a Universal Occurrence? Further Evidence From Asian Stock Markets," Finance 0308001, University Library of Munich, Germany.
    9. Ammermann, Peter A. & Patterson, Douglas M., 2003. "The cross-sectional and cross-temporal universality of nonlinear serial dependencies: Evidence from world stock indices and the Taiwan Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 11(2), pages 175-195, April.
    10. Rodrigo Aranda & Patricio Jaramillo, 2008. "Nonlinear Dynamic in the Chilean Stock Market: Evidence from Returns and Trading Volume," Working Papers Central Bank of Chile 463, Central Bank of Chile.
    11. de Lima, Pedro J. F., 1997. "On the robustness of nonlinearity tests to moment condition failure," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 251-280.
    12. Charles, Amelie & Darne, Olivier & Kim, Jae, 2016. "Stock Return Predictability: Evaluation based on Prediction Intervals," MPRA Paper 70143, University Library of Munich, Germany.
    13. Holger Dette & Marc Hallin & Tobias Kley & Stanislav Volgushev, 2011. "Of Copulas, Quantiles, Ranks and Spectra - An L1-Approach to Spectral Analysis," Working Papers ECARES ECARES 2011-038, ULB -- Universite Libre de Bruxelles.
    14. Kian-Ping Lim & Melvin J. Hinich, 2005. "Cross-temporal universality of non-linear dependencies in Asian stock markets," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-6.
    15. Aghababa, Hajar & Barnett, William A., 2016. "Dynamic structure of the spot price of crude oil: does time aggregation matter?," Energy Economics, Elsevier, vol. 59(C), pages 227-237.
    16. Bai, Zhidong & Hui, Yongchang & Wong, Wing-Keung, 2012. "New Non-Linearity Test to Circumvent the Limitation of Volterra Expansion," MPRA Paper 41872, University Library of Munich, Germany.
    17. Refk Selmi & Aviral Kumar Tiwari & Shawkat Hammoudeh, 2018. "Efficiency or speculation? A dynamic analysis of the Bitcoin market," Economics Bulletin, AccessEcon, vol. 38(4), pages 2037-2046.
    18. Gustavo Deco & Diego Vidaurre & Morten L. Kringelbach, 2021. "Revisiting the global workspace orchestrating the hierarchical organization of the human brain," Nature Human Behaviour, Nature, vol. 5(4), pages 497-511, April.
    19. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.
    20. Melvin. J. Hinich & Phillip Wild & John Foster, 2010. "Testing for the Existence of a Generalized Wiener Process- the Case of Stock Prices," Discussion Papers Series 408, School of Economics, University of Queensland, Australia.

    More about this item

    Keywords

    Bispectrum; VAR; Nonlinear; Episodic nonlinearity; Gaussian; Skewness function; MARS; L1 estimation; MINIMAX estimation; Leverage plot; ACE; GAM; Projection pursuit;
    All these keywords.

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    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:spr:compst:v:26:y:2011:i:1:p:77-93. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.