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Detecting multiple outliers in linear regression using a cluster method combined with graphical visualization

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  • Sung-Soo Kim
  • W. Krzanowski

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  • Sung-Soo Kim & W. Krzanowski, 2007. "Detecting multiple outliers in linear regression using a cluster method combined with graphical visualization," Computational Statistics, Springer, vol. 22(1), pages 109-119, April.
    • Handle: RePEc:spr:compst:v:22:y:2007:i:1:p:109-119
    DOI: 10.1007/s00180-007-0026-3
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    References listed on IDEAS

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    1. J. C. Gower & G. J. S. Ross, 1969. "Minimum Spanning Trees and Single Linkage Cluster Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 18(1), pages 54-64, March.
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    Cited by:

    1. Menjoge, Rajiv S. & Welsch, Roy E., 2010. "A diagnostic method for simultaneous feature selection and outlier identification in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3181-3193, December.
    2. Yingli Pan & Zhan Liu & Guangyu Song, 2021. "Outlier detection under a covariate-adjusted exponential regression model with censored data," Computational Statistics, Springer, vol. 36(2), pages 961-976, June.
    3. M. Habshah & M. R. Norazan & A.H.M. Rahmatullah Imon, 2009. "The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(5), pages 507-520.
    4. Sung-Soo Kim & Sung Park & W. J. Krzanowski, 2008. "Simultaneous variable selection and outlier identification in linear regression using the mean-shift outlier model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(3), pages 283-291.
    5. Nikolas Kuschnig & Gregor Zens & Jesús Crespo Cuaresma, 2021. "Hidden in Plain Sight: Influential Sets in Linear Models," CESifo Working Paper Series 8981, CESifo.

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