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Modeling and Smoothing Unequally Spaced Sequence Data

Author

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  • Piet Jong

    ()

  • Sonia Mazzi

    ()

Abstract

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Suggested Citation

  • Piet Jong & Sonia Mazzi, 2001. "Modeling and Smoothing Unequally Spaced Sequence Data," Statistical Inference for Stochastic Processes, Springer, vol. 4(1), pages 53-71, January.
  • Handle: RePEc:spr:sistpr:v:4:y:2001:i:1:p:53-71
    DOI: 10.1023/A:1017510420686
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    File URL: http://hdl.handle.net/10.1023/A:1017510420686
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    References listed on IDEAS

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    1. Lavielle, Marc, 1999. "Detection of multiple changes in a sequence of dependent variables," Stochastic Processes and their Applications, Elsevier, vol. 83(1), pages 79-102, September.
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    Cited by:

    1. Rob J Hyndman & Maxwell L. King & Ivet Pitrun & Baki Billah, 2002. "Local Linear Forecasts Using Cubic Smoothing Splines," Monash Econometrics and Business Statistics Working Papers 10/02, Monash University, Department of Econometrics and Business Statistics.
    2. Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.

    More about this item

    Keywords

    Kalman filter; Splines; Smoothing; State space model;

    Statistics

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