We consider one-sided Grubbs's statistics for a normal sample of the size n. These statistics are extreme studentized deviations of the observations from the sample mean. One abnormal observation (outlier) is assumed in the sample, its number is unknown. We consider the case when the outlier differs from other observations in values of population mean and dispersion, i. e., shift and scale parameters. We construct a copula-function by an inversion method from the joint distribution of Grubbs's statistics, it depends on three parameters: shift and scale parameters and n. It is proved that for Grubbs's copula-function, the coefficients of the upper-left and lower-right tail dependencies are equal each other. Moreover, their value is independent of the shift and scale parameters but it depends on parameter n. The dependence in the tails of the distribution of the three-parameter Grubbs's copula coincides with the dependence in the tails of the joint distribution of one-sided Grubbs's statistics calculated from the normal sample without outlier.

我们考虑大小为n的正常样本的单面Grubbs统计量。这些统计数据是观测值与样本均值之间的极端学生偏差。样本中假设有一个异常观测值（异常值），其数量未知。我们考虑当异常值在总体均值和离散值（即i）与其他观察值不同时的情况。例如，移位和缩放参数。我们根据Grubbs统计量的联合分布，通过反演方法构造一个copula函数，它取决于三个参数：shift和scale参数以及n。对于Grubbs的copula函数，证明了左上和右下尾部依赖项的系数彼此相等。此外，它们的值与shift和scale参数无关，但取决于参数n。三参数Grubbs系的分布在尾部的依存性与从正常样本计算而没有异常值的单侧Grubbs统计的联合分布的尾部相符合。