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Finding multivariate outliers with FastPCS

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  • Vakili, Kaveh
  • Schmitt, Eric

Abstract

The Projection Congruent Subset (PCS) is a new method for finding multivariate outliers. Like many other outlier detection procedures, PCS searches for a subset which minimizes a criterion. The difference is that the new criterion was designed to be insensitive to the outliers. PCS is supported by FastPCS, a fast and affine equivariant algorithm which is also detailed. Both an extensive simulation study and a real data application from the field of engineering show that FastPCS performs better than its competitors.

Suggested Citation

  • Vakili, Kaveh & Schmitt, Eric, 2014. "Finding multivariate outliers with FastPCS," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 54-66.
    • Handle: RePEc:eee:csdana:v:69:y:2014:i:c:p:54-66
    DOI: 10.1016/j.csda.2013.07.021
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    References listed on IDEAS

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    1. Rousseeuw, Peter J., 1994. "Unconventional features of positive-breakdown estimators," Statistics & Probability Letters, Elsevier, vol. 19(5), pages 417-431, April.
    2. Todorov, Valentin & Filzmoser, Peter, 2009. "An Object-Oriented Framework for Robust Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i03).
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    Cited by:

    1. Daniel Kosiorowski & Dominik Mielczarek & Jerzy P. Rydlewski & Małgorzata Snarska, 2018. "Generalized Exponential Smoothing In Prediction Of Hierarchical Time Series," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 331-350, June.
    2. Kosiorowski Daniel & Mielczarek Dominik & Rydlewski Jerzy P. & Snarska Małgorzata, 2018. "Generalized Exponential Smoothing In Prediction Of Hierarchical Time Series," Statistics in Transition New Series, Statistics Poland, vol. 19(2), pages 331-350, June.
    3. Sevvandi Kandanaarachchi & Rob J Hyndman, 2019. "Dimension Reduction For Outlier Detection Using DOBIN," Monash Econometrics and Business Statistics Working Papers 17/19, Monash University, Department of Econometrics and Business Statistics.
    4. Schmitt, Eric & Öllerer, Viktoria & Vakili, Kaveh, 2014. "The finite sample breakdown point of PCS," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 214-220.

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