Krause Lennard, Niepötter Benedikt, Schürmann Christian J, Stalke Dietmar, Herbst-Irmer Regine
Institut für Anorganische Chemie, Universität Göttingen, Tammannstraße 4, Göttingen 37077, Germany.
IUCrJ. 2017 May 24;4(Pt 4):420-430. doi: 10.1107/S2052252517005103. eCollection 2017 Jul 1.
A cross-validation method is supplied to judge between various strategies in multipole refinement procedures. Its application enables straightforward detection of whether the refinement of additional parameters leads to an improvement in the model or an overfitting of the given data. For all tested data sets it was possible to prove that the multipole parameters of atoms in comparable chemical environments should be constrained to be identical. In an automated approach, this method additionally delivers parameter distributions of different refinements. These distributions can be used for further error diagnostics, to detect erroneously defined parameters or incorrectly determined reflections. Visualization tools show the variation in the parameters. These different refinements also provide rough estimates for the standard deviation of topological parameters.
提供了一种交叉验证方法,用于在多极细化程序中的各种策略之间进行判断。它的应用能够直接检测出额外参数的细化是否会导致模型的改进或给定数据的过拟合。对于所有测试数据集,都有可能证明在可比化学环境中原子的多极参数应被约束为相同。在自动化方法中,该方法还能给出不同细化的参数分布。这些分布可用于进一步的误差诊断,以检测错误定义的参数或错误确定的反射。可视化工具展示了参数的变化。这些不同的细化还为拓扑参数的标准偏差提供了粗略估计。