论文标题
关于在线变更点检测的注释
A Note on Online Change Point Detection
论文作者
论文摘要
我们研究了单变量非参数设置中的顺序变化点估计和检测，其中收集了具有共同方差因子和分段恒定但未知的均值的独立观察结果。我们开发了一种简单的基于CUSUM的方法，该方法可以证明可以控制错误警报的概率或平均运行长度，同时从最小化意义上最小化检测延迟。我们允许所有模型参数变化，以捕获手头问题的广泛统计硬度。我们进一步展示了我们的方法论如何顺序估算多个变更点的情况。
We investigate sequential change point estimation and detection in univariate nonparametric settings, where a stream of independent observations from sub-Gaussian distributions with a common variance factor and piecewise-constant but otherwise unknown means are collected. We develop a simple CUSUM-based methodology that provably control the probability of false alarms or the average run length while minimizing, in a minimax sense, the detection delay. We allow for all the model parameters to vary in order to capture a broad range of levels of statistical hardness for the problem at hand. We further show how our methodology is applicable to the case in which multiple change points are to be estimated sequentially.
