IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v36y2001i2p179-207.html
   My bibliography  Save this article

Selecting sub-set autoregressions from outlier contaminated data

Author

Listed:
  • H. Glendinning, Richard

Abstract

No abstract is available for this item.

Suggested Citation

  • H. Glendinning, Richard, 2001. "Selecting sub-set autoregressions from outlier contaminated data," Computational Statistics & Data Analysis, Elsevier, vol. 36(2), pages 179-207, April.
    • Handle: RePEc:eee:csdana:v:36:y:2001:i:2:p:179-207
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(00)00038-4
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Jack H. W. Penm & R. D. Terrell, 1982. "On The Recursive Fitting Of Subset Autoregressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(1), pages 43-59, January.
    2. Hector Allende & Siegfried Heiler, 1992. "Recursive Generalized M Estimates For Autoregressive Moving‐Average Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(1), pages 1-18, January.
    3. Chen, Zhao-Guo & Ni, Jun-Yuan, 1989. "Subset regression time series and its modeling procedures," Journal of Multivariate Analysis, Elsevier, vol. 31(2), pages 266-288, November.
    4. Douglas M. Hawkins & Jeffrey S. Simonoff, 1993. "High Breakdown Regression and Multivariate Estimation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(2), pages 423-432, June.
    5. Gwo‐Hsing Yu & Yow‐Chang Lin, 1991. "A Methodology For Selecting Subset Autoregressive Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 12(4), pages 363-373, July.
    6. Pena, Daniel, 1990. "Influential Observations in Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 235-241, April.
    7. G. Masarotto, 1987. "Robust Identification of Autoregressive Moving Average Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(2), pages 214-220, June.
    8. Xichuan Zhang & R. Deane Terrell, 1997. "Projection Modulus: A New Direction For Selecting Subset Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(2), pages 195-212, March.
    9. V. Haggan & O. B. Oyetunji, 1984. "On The Selection Of Subset Autoregressive Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 5(2), pages 103-113, March.
    10. Hotta, Luiz Koodi, 1993. "The effect of additive outliers on the estimates from aggregated and disaggregated ARIMA models," International Journal of Forecasting, Elsevier, vol. 9(1), pages 85-93, April.
    11. Jack H. W. Penm & Jammie H. Penm & R. D. Terrell, 1993. "The Recursive Fitting Of Subset Varx Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(6), pages 603-619, November.
    12. Ledolter, Johannes, 1989. "The effect of additive outliers on the forecasts from ARIMA models," International Journal of Forecasting, Elsevier, vol. 5(2), pages 231-240.
    13. Hoeting, Jennifer & Raftery, Adrian E. & Madigan, David, 1996. "A method for simultaneous variable selection and outlier identification in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 22(3), pages 251-270, July.
    14. Suzanne Sommer & Richard M. Huggins, 1996. "Variables Selection Using the Wald Test and a Robust CP," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(1), pages 15-29, March.
    15. Winker, Peter, 1995. "Identification of multivariate AR-models by threshold accepting," Computational Statistics & Data Analysis, Elsevier, vol. 20(3), pages 295-307, September.
    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. R. H. Glendinning, 2000. "Estimating the Inverse Autocorrelation Function from Outlier Contaminated Data," Computational Statistics, Springer, vol. 15(4), pages 541-565, December.
    2. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    3. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2004. "Estimating threshold subset autoregressive moving-average models by genetic algorithms," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 39-61.
    4. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    5. Justel, Ana & Peña, Daniel & Sánchez, María Jesús, 1994. "Grupos atípicos en modelos econométricos," DES - Documentos de Trabajo. Estadística y Econometría. DS 10755, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Hella, Heikki, 2003. "On robust ESACF identification of mixed ARIMA models," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2003_027.
    7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    8. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Siniksaran, Enis, 2008. "A geometric interpretation of Mallows' Cp statistic and an alternative plot in variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3459-3467, March.
    10. H. W. Wayne Yang & Po-Wei Shen & An-Sing Chen, 2020. "Trimming Effects And Momentum Investing," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 14(2), pages 73-87.
    11. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    12. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    13. James C. Rockey, 2007. "Which Democracies Pay Higher Wages?," Bristol Economics Discussion Papers 07/600, School of Economics, University of Bristol, UK.
    14. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    15. John S.nChipman & Peter Winker, "undated". "Optimal Industrial Classification in a Dynamic Model of Price Adjustment," Computing in Economics and Finance 1996 _013, Society for Computational Economics.
    16. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
    17. Min-Hsien Chiang & Ray Yeutien Chou & Li-Min Wang, 2016. "Outlier Detection in the Lognormal Logarithmic Conditional Autoregressive Range Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 126-144, February.
    18. Bali, Rakesh & Guirguis, Hany, 2007. "Extreme observations and non-normality in ARCH and GARCH," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 332-346.
    19. Menjoge, Rajiv S. & Welsch, Roy E., 2010. "A diagnostic method for simultaneous feature selection and outlier identification in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3181-3193, December.
    20. Francisco JA Cysneiros, 2018. "Symmetric Regression Model for Temporal Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(2), pages 44-45, February.

    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:eee:csdana:v:36:y:2001:i:2:p:179-207. 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.