Autoregressive models are a class of time series models that are important in both applied and theoretical statistics. Typically, inferential devices such as confidence sets and hypothesis tests for time series models require nuanced asymptotic arguments and constructions. We present a simple alternative to such arguments that allow for the construction of finite sample valid inferential devices, using a data splitting approach. We prove the validity of our constructions, as well as the validity of related sequential inference tools. A set of simulation studies are presented to demonstrate the applicability of our methodology.
翻译:自动递减模型是一系列时间序列模型,在应用和理论统计中都很重要,一般来说,信心组和时间序列模型假设测试等推论装置需要细微的无症状论证和构思。我们提出一个简单的替代论点,以便利用数据分离的方法,建造有限的有效推定装置样本。我们证明了我们构造的正确性以及相关的顺序推论工具的有效性。我们提出了一套模拟研究,以证明我们方法的适用性。