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Expectation‐Maximization Algorithms And The Estimation Of Time Series Models In The Presence Of Outliers

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  • Bovas Abraham
  • Alice Chuang

Abstract

. The expectation‐maximization algorithm is reviewed briefly. The algorithm is applied to time series situations where outliers may be present. An approximation of the algorithm is considered to reduce the computational complexity. Examples are given to illustrate the application of this algorithm.

Suggested Citation

  • Bovas Abraham & Alice Chuang, 1993. "Expectation‐Maximization Algorithms And The Estimation Of Time Series Models In The Presence Of Outliers," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(3), pages 221-234, May.
    • Handle: RePEc:bla:jtsera:v:14:y:1993:i:3:p:221-234
    DOI: 10.1111/j.1467-9892.1993.tb00140.x
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    Cited by:

    1. Mátyás Barczy & Márton Ispány & Gyula Pap & Manuel Scotto & Maria Silva, 2012. "Additive outliers in INAR(1) models," Statistical Papers, Springer, vol. 53(4), pages 935-949, November.
    2. Chareka, Patrick & Matarise, Florance & Turner, Rolf, 2006. "A test for additive outliers applicable to long-memory time series," Journal of Economic Dynamics and Control, Elsevier, vol. 30(4), pages 595-621, April.

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