Using the ordinal pattern concept in permutation entropy, we propose a model sufficiency test to study a given model's point prediction accuracy. Compared to some classical model sufficiency tests, such as the Broock et al.'s (1996) test, our proposal does not require a sufficient model to eliminate all structures exhibited in the estimated residuals. When the innovations in the investigated data's underlying dynamics show a certain structure, such as higher-moment serial dependence, the Broock et al.'s (1996) test can lead to erroneous conclusions about the sufficiency of point predictors. Due to the structured innovations, inconsistency between the model sufficiency tests and prediction accuracy criteria can occur. Our proposal fills in this incoherence between model and prediction evaluation approaches and remains valid when the underlying process has non-white additive innovation.
翻译:使用变异性变异性变异性变异性变异性变异性时,我们提出一个模型充裕性测试,以研究某一模型的点预测准确性。与一些古典模型的充足性测试,如Broock等人(1996年)的测试相比,我们的提案并不需要一个足够的模型来消除估计剩余物中显示的所有结构。当调查数据基本动态的革新显示出某种结构,如更高度的移动性序列依赖性时,Broock等人(1996年)的测试可能导致对点预测器的充足性得出错误的结论。由于有结构的创新,模型的充足性测试和预测准确性标准之间可能出现不一致。我们的提案填补了模型和预测评价方法之间的这种不一致,并且在基本过程有非白添加性创新时仍然有效。