Abstract: In their article, Greven and Scheipl describe an impressively general framework for performing functional regression that builds upon the generalized additive modelling framework. Over the past number of years, my collaborators and I have also been developing a general framework for functional regression, functional mixed models, which shares many similarities with this framework, but has many differences as well. In this discussion, I compare and contrast these two frameworks, to hopefully illuminate characteristics of each, highlighting their respective strengths and weaknesses, and providing recommendations regarding the settings in which each approach might be preferable.

中文翻译：

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两种通用函数回归建模框架的比较与对比

摘要：在他们的文章中，Greven 和 Scheipl 描述了一个令人印象深刻的通用框架，用于执行基于广义加法建模框架的函数回归。在过去的几年里，我和我的合作者也一直在开发函数回归的通用框架，函数混合模型，它与这个框架有许多相似之处，但也有许多不同之处。在本次讨论中，我比较和对比了这两个框架，希望能够阐明每个框架的特征，突出它们各自的优势和劣势，并提供有关每种方法可能更可取的设置的建议。