Hypothesis-error (or “HE”) plots, introduced by Friendly (J Stat Softw 17(6):1–42, 2006a; J Comput Graph Stat 16:421–444, 2006b), permit the visualization of hypothesis tests in multivariate linear models by representing hypothesis and error matrices of sums of squares and cross-products as ellipses. This paper describes the implementation of these methods in the heplots package for R, as well as their extension, for example from two to three dimensions and by scaling hypothesis ellipses and ellipsoids in a natural manner relative to error.
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机译：由Friendly（J Stat Softw 17（6）：1-42，2006a; J Comput Graph Stat 16：421-444，2006b）引入的假设-错误（或“ HE”）图允许多变量假设检验的可视化通过将平方和叉积和的假设和误差矩阵表示为椭圆来建立线性模型。本文描述了这些方法在R的heplots包中的实现以及它们的扩展，例如从二维扩展到三维，并通过相对于误差的自然方式缩放假设椭圆和椭球。
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