Regression model

Robusna Mahalanobisova udaljenost

Robusna Mahalanobisova udaljenost označava multivarijantne autlajere merenjem koliko svaka opservacija leži od centra podataka koristeći robusnu procenu kovarijacije. Ona se nadograđuje na robusni okvir udaljenosti Rousseeuwa i Van Zomerena (1990) i pristup multivarijantnom otkrivanju autlajera Filzmosera, Garreta i Rajmana (2005), zamenjujući klasični prosek i kovarijansnu matricu procenom najmanjeg determinanta kovarijacije (MCD) tako da sami autlajeri ne iskrivljuju udaljenost.

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Izvori

  1. Rousseeuw, P. J. & Van Zomeren, B. C. (1990). Unmasking Multivariate Outliers and Leverage Points. Journal of the American Statistical Association, 85(411), 633-639. DOI: 10.1080/01621459.1990.10474920
  2. Filzmoser, P., Garrett, R. G. & Reimann, C. (2005). Multivariate Outlier Detection in Exploration Geochemistry. Computational Statistics & Data Analysis, 49(2), 561-587. DOI: 10.1016/j.cageo.2004.11.013

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ScholarGate. (2026, June 1). Robust Mahalanobis Distance (MCD-based Multivariate Outlier Detection). ScholarGate. https://scholargate.app/sr/statistics/mahalanobis-robust

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ScholarGateRobust Mahalanobis Distance (Robust Mahalanobis Distance (MCD-based Multivariate Outlier Detection)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/statistics/mahalanobis-robust · Skup podataka: https://doi.org/10.5281/zenodo.20539026