The R package robusTest offers corrected versions of several common tests in bivariate statistics. We point out the limitations of these tests in their classical versions, some of which are well known such as robustness or calibration problems, and provide simple alternatives that can be easily used instead. The classical tests and theirs robust alternatives are compared through a small simulation study. The latter emphasizes the superiority of robust versions of the test of interest. Finally, an illustration of correlation's tests on a real data set is also provided.

翻译：R包robusTest提供了双变量统计学中几种常见检验的修正版本。我们指出了这些检验在经典版本中的局限性（其中一些广为人知，如稳健性或校准问题），并提供了可轻松替代使用的简单方案。通过一项小型模拟研究，对经典检验及其稳健替代方案进行了比较，结果凸显了目标检验稳健版本的优越性。最后，还提供了相关性检验在真实数据集上的应用实例。