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Prediction with incomplete past and interpolation of missing values

Author

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  • Cheng, R.
  • Pourahmadi, M.

Abstract

A generalized innovation algorithm is used to solve the problems of prediction of future values based on incomplete past and interpolation of missing values of a stationary time series. The emphasis is on the computational aspects and the proposed method is particularly useful when there are several missing values with arbitrary patterns.

Suggested Citation

  • Cheng, R. & Pourahmadi, M., 1997. "Prediction with incomplete past and interpolation of missing values," Statistics & Probability Letters, Elsevier, vol. 33(4), pages 341-346, May.
    • Handle: RePEc:eee:stapro:v:33:y:1997:i:4:p:341-346
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    References listed on IDEAS

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    1. Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
    2. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
    3. S. R. Brubacher & G. Tunnicliffe Wilson, 1976. "Interpolating Time Series with Application to the Estimation of Holiday Effects on Electricity Demand," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 25(2), pages 107-116, June.
    4. Mohsen Pourahmadi, 1989. "Estimation And Interpolation Of Missing Values Of A Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 10(2), pages 149-169, March.
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    Cited by:

    1. Pascal Bondon, 2005. "Influence of Missing Values on the Prediction of a Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 519-525, July.
    2. Cheng, Raymond, 2015. "Prediction of stationary Gaussian random fields with incomplete quarterplane past," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 245-258.
    3. Tucker S. McElroy & Dimitris N. Politis, 2022. "Optimal linear interpolation of multiple missing values," Statistical Inference for Stochastic Processes, Springer, vol. 25(3), pages 471-483, October.
    4. Kohli, P. & Pourahmadi, M., 2014. "Some prediction problems for stationary random fields with quarter-plane past," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 112-125.
    5. Bondon, Pascal, 2002. "Prediction with incomplete past of a stationary process," Stochastic Processes and their Applications, Elsevier, vol. 98(1), pages 67-76, March.

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