Discrete but ordered covariates are quite common in applied statistics, and some regularized fitting procedures have been proposed for proper handling of ordinal predictors in statistical modeling. In this study, we show how quadratic penalties on adjacent dummy coefficients of ordinal predictors proposed in the literature can be incorporated in the framework of generalized additive models, making tools for statistical inference developed there available for ordinal predictors as well. Motivated by an application from neonatal medicine, we discuss whether results obtained when constructing confidence intervals and testing significance of smooth terms in generalized additive models are useful with ordinal predictors/penalties as well.

翻译：在应用统计中,分解但有定序的共变体相当常见,并且已经提议了一些正规化的安装程序,以便在统计模型中适当处理正态预测器。在本研究中,我们展示了如何将文献中提议的对相邻正态预测器的隐形系数的二次处罚纳入通用添加模型框架,使那里为正态预测器开发的统计推论工具也能够提供。受新生儿医学应用的驱动,我们讨论了在建立互信间隔和测试通用添加剂模型中平稳条件的重要性时所取得的成果是否与正态预测器/药物一起有用。