A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters
一般参数序贯变点检测的似然比方法
In this article, we propose a new approach for sequential monitoring of a general class of parameters of a d-dimensional time series, which can be estimated by approximately linear functionals of the empirical distribution function. We consider a closed-end method, which is motivated by the likelihood ratio test principle and compare the new method with two alternative procedures. We also incorporate self-normalization such that estimation of the long-run variance is not…