This work describes the R package GET that implements global envelopes for a general set of $d$-dimensional vectors $T$ in various applications. A $100(1-\alpha)$\% global envelope is a band bounded by two vectors such that the probability that $T$ falls outside this envelope in any of the $d$ points is equal to $\alpha$. Global means that the probability is controlled simultaneously for all the $d$ elements of the vectors. The global envelopes can be employed for central regions of functional or multivariate data, for graphical Monte Carlo and permutation tests where the test statistic is multivariate or functional, and for global confidence and prediction bands. Intrinsic graphical interpretation property is introduced for global envelopes. The global envelopes included in the GET package have the property, which particularly helps to interpret the test results, by having a graphical interpretation that shows the reasons of rejection of the tested hypothesis. Examples of different uses of global envelopes and their implementation in the GET package are presented, including global envelopes for single and several one- or two-dimensional functions, Monte Carlo goodness-of-fit tests for simple and composite hypotheses, comparison of distributions, functional analysis of variance, and functional linear model, and confidence bands in polynomial regression.

翻译：摘要：本文描述了R语言包GET，该包实现了通用$d$维向量$T$集合在各种应用中的全局包络。一个$100(1-\alpha)$%全局包络是由两个向量界定的带状区域，使得向量$T$在任意$d$个点中落在此包络之外的概率等于$\alpha$。全局性意味着该概率同时控制了向量的所有$d$个元素。全局包络可用于函数型或多变量数据的中心区域、检验统计量为多变量或函数型的图形化蒙特卡洛与置换检验，以及全局置信带与预测带。本文引入了全局包络的内在图形解释性质。GET包中的全局包络具有该性质，通过提供展示被检验假设被拒绝原因的图形化解释，尤其有助于解释检验结果。文中给出了全局包络的不同应用示例及其在GET包中的实现，包括单个和多个一维或二维函数的全局包络、简单与复合假设的蒙特卡洛拟合优度检验、分布比较、函数型方差分析、函数型线性模型，以及多项式回归中的置信带。