Electronic Journal of Statistics

Discussion of “High-dimensional autocovariance matrices and optimal linear prediction”

Rob J. Hyndman

Full-text: Open access

Abstract

I propose new ACF and PACF plots based on the autocovariance estimators of McMurry and Politis. I also show that the forecasting methods they propose perform poorly compared to some relatively simple autoregression algorithms already available.

Article information

Source
Electron. J. Statist. Volume 9, Number 1 (2015), 792-796.

Dates
Received: October 2014
First available in Project Euclid: 3 November 2014

Permanent link to this document
http://projecteuclid.org/euclid.ejs/1415023525

Digital Object Identifier
doi:10.1214/14-EJS953

Mathematical Reviews number (MathSciNet)
MR3331858

Zentralblatt MATH identifier
06427967

Keywords
Autocorrelation autoregression data visualization forecasting serial correlation time series graphics

Citation

Hyndman, Rob J. Discussion of “High-dimensional autocovariance matrices and optimal linear prediction”. Electron. J. Statist. 9 (2015), no. 1, 792--796. doi:10.1214/14-EJS953. http://projecteuclid.org/euclid.ejs/1415023525.


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References

  • Hurvich, C. & Tsai, C. (1997), ‘Selection of a multistep linear predictor for short time series’, Statistica Sinica 7, 395–406.
  • Hyndman, R. J. & Khandakar, Y. (2008), ‘Automatic time series forecasting: The forecast package for R’, Journal of Statistical Software 26(3), 1–22.
  • Makridakis, S. G., Wheelwright, S. C. & Hyndman, R. J. (1998), Forecasting: Methods and Applications, 3rd edition edn, John Wiley and Sons, New York.
  • McMurry, T. L. & Politis, D. N. (2010), ‘Banded and tapered estimates for autocovariance matrices and the linear process bootstrap’, J. Time Series Analysis 31(6), 471–482.
  • Morettin, P. A. (1984), ‘The Levinson algorithm and its applications in time series analysis’, International Statistical Review 52(1), 83–92.
  • R Core Team (2014), R: A Language and Environment for Statistical Computing, Vienna, Austria. http://www.r-project.org

See also

  • Related item: Timothy L. McMurry, Dimitris N. Politis (2015). High-dimensional autocovariance matrices and optimal linear prediction. Electron. J. Statist. Vol. 9, 753–788.