期刊
STATISTICA NEERLANDICA
卷 56, 期 2, 页码 214-232出版社
BLACKWELL PUBL LTD
DOI: 10.1111/1467-9574.00195
关键词
nonparametric; depth functions; location; trimmed mean; scale; interquartile region; kurtosis
Despite the absence of a natural ordering of Euclidean space for dimensions greater than one, the effort to define vector-valued quantile functions for multivariate distributions has generated several approaches. To support greater discrimination in comparing, selecting and using such functions, we introduce relevant criteria, including a notion of median-oriented quantile function. On this basis we compare recent quantile approaches and several multivariate versions of trimmed mean and interquartile range. We also discuss a univariate generalized quantile approach that enables particular features of multivariate distributions, for example scale and kurtosis, to be studied by two-dimensional plots. Methods based on statistical depth functions are found to be especially attractive for quantile-based multivariate inference.
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