论文标题
异常：时间序列数据中异常结构的检测
anomaly : Detection of Anomalous Structure in Time Series Data
论文作者
论文摘要
异常检测中的当代挑战之一是在数据序列或时间序列中检测并区分点和集体异常。已经开发出异常软件包为用户提供异常检测方法的选择，尤其是提供了最近提出的集体和指向异常检测算法的异常家族的实现。本文介绍了实施的方法，同时还强调了它们在模拟数据中的应用以及软件包中包含的真实数据示例。
One of the contemporary challenges in anomaly detection is the ability to detect, and differentiate between, both point and collective anomalies within a data sequence or time series. The anomaly package has been developed to provide users with a choice of anomaly detection methods and, in particular, provides an implementation of the recently proposed Collective And Point Anomaly family of anomaly detection algorithms. This article describes the methods implemented whilst also highlighting their application to simulated data as well as real data examples contained in the package.
