Bootstrapping Spatial Median for Location Problems |
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Authors: | Myoungshic Jhun SeungJun Shin |
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Institution: | 1. Department of Statistics , Korea University , Seoul , Korea jhun@korea.ac.kr;3. Department of Statistics , North Carolina State University , Raleigh , North Carolina , USA |
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Abstract: | In multivariate location problems, the sample mean is most widely used, having various advantages. It is, however, very sensitive to outlying observations and inefficient for data from heavy tailed distributions. In this situation, the spatial median is more robust than the sample mean and could be a reasonable alternative. We reviewed several spatial median based testing methods for multivariate location and compared their significance level and power through Monte Carlo simulations. The results show that bootstrap method is efficient for the estimation of the covariance matrix of the sample spatial median. We also proposed bootstrap simultaneous confidence intervals based on the spatial median for multiple comparisons in the multi-sample case. |
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Keywords: | Bootstrap Multivariate location Simultaneous confidence interval Spatial median |
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