论文标题
统计模型的合适性测试
A Goodness-of-Fit Test for Statistical Models
论文作者
论文摘要
统计模型在理解大规模数据（统计推断）的潜在机制和预测未来（统计预测）方面起着基本作用。尽管所有模型都是错误的，但研究人员会尽力使其中一些有用。这里的问题是如何衡量统计模型对数据的有用性？这是统计预测的关键。测试观察结果是否遵循提出的统计模型的重要统计问题仅吸引了相对较少的注意力。在本文中，我们通过通过两样本分布比较建立联系，为此问题提出了一个新的框架。提出的方法可以应用于评估广泛的模型。给出了示例以显示所提出的方法的性能。
Statistical modeling plays a fundamental role in understanding the underlying mechanism of massive data (statistical inference) and predicting the future (statistical prediction). Although all models are wrong, researchers try their best to make some of them be useful. The question here is how can we measure the usefulness of a statistical model for the data in hand? This is key to statistical prediction. The important statistical problem of testing whether the observations follow the proposed statistical model has only attracted relatively few attentions. In this paper, we proposed a new framework for this problem through building its connection with two-sample distribution comparison. The proposed method can be applied to evaluate a wide range of models. Examples are given to show the performance of the proposed method.
