Diagnosis of Observations after Fit of Multivariate Skew t-Distribution: Identification of Outliers and Edge Observations from Asymmetric Data

Kim, Seung-Gu

  • Received : 2012.10.22
  • Accepted : 2012.11.08
  • Published : 2012.12.31


This paper presents a method for the identification of "edge observations" located on a boundary area constructed by a truncation variable as well as for the identification of outliers and the after fit of multivariate skew $t$-distribution(MST) to asymmetric data. The detection of edge observation is important in data analysis because it provides information on a certain critical area in observation space. The proposed method is applied to an Australian Institute of Sport(AIS) dataset that is well known for asymmetry in data space.


Multivariate skew t-distribution;edge observation;outlier;ECM algorithm


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