Compositional data carry their relevant information in the relationships (logratios) between the compositional parts. It is shown how this source of information can be used in regression modeling, where the composition could either form the response, or the explanatory part, or even both. An essential step to set up a regression model is the way how the composition(s) enter the model. Here, balance coordinates will be constructed that support an interpretation of the regression coefficients and allow for testing hypotheses of subcompositional independence. Both classical least-squares regression and robust MM regression are treated, and they are compared within different regression models at a real data set from a geochemical mapping project.

组成数据在组成部分之间的关​​系（对数）中携带其相关信息。它显示了如何在回归建模中使用此信息源，其中组合可以构成响应，也可以构成解释部分，甚至可以构成两者。建立回归模型的重要步骤是组成成分如何进入模型。在这里，将构建平衡坐标，以支持回归系数的解释并允许测试子成分独立性的假设。处理了经典最小二乘回归和鲁棒MM回归，并在来自地球化学测绘项目的真实数据集的不同回归模型中进行了比较。