The potential of location-shift models to find adequate models between the proportional odds model and the non-proportional odds model is investigated. It is demonstrated that these models are very useful in ordinal modelling. While proportional odds models are often too simple, non-proportional odds models are typically unnecessary complicated and seem widely dispensable. In addition, the class of location-shift models is extended to allow for smooth effects. The additive location-shift model contains two functions for each explanatory variable, one for the location and one for dispersion. It is much sparser than hard-to-handle additive models with category-specific covariate functions but more flexible than common vector generalised additive models. An R package is provided that is able to fit parametric and additive location-shift models.

中文翻译：

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基于参数和加性位置转移方法的稀疏序数回归模型

研究了位置偏移模型在比例优势模型和非比例优势模型之间找到适当模型的潜力。证明这些模型在序数建模中非常有用。虽然比例赔率模型通常过于简单，但非比例赔率模型通常不必要的复杂并且似乎广泛可有可无。此外，还扩展了位置偏移模型类以实现平滑效果。加性位置偏移模型包含每个解释变量的两个函数，一个用于位置，一个用于分散。它比具有特定类别协变量函数的难以处理的加法模型稀疏得多，但比常见的向量广义加法模型更灵活。提供了一个 R 包，它能够拟合参数和附加位置偏移模型。