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:本文介绍了R语言中GET包的实现,用于各种应用中的一般$d$维向量$T$的全局包络。一个$100(1-\alpha)$\%的全局包络是由两个向量界定的带状区域,使得在$d$个点中的任意一点,$T$落在此包络之外的概率等于$\alpha$。全局意味着对所有向量元素同时进行概率控制。全局包络可用于多元或函数数据中心区域、图形化蒙特卡罗和置换检验,其中检验统计量是多元或函数形式,以及全局置信和预测带。本文引入了全局包络的本质图形解释性。GET包含的全局包络具有此属性,这特别有助于解释测试结果,因为它具有图形解释,显示测试假设被拒绝的原因。文中提供了不同全局包络的使用示例和其在GET包中的实现,包括用于单个和多个一维或二维函数的全局包络、蒙特卡罗拟合度检验的简单和复合假设、分布比较、函数方差分析、函数线性模型和多项式回归置信带。