We consider the change-point detection in multivariate continuous and integer valued time series. We propose a Wald-type statistic based on the estimator performed by a general contrast function; which can be constructed from the likelihood, a quasi-likelihood, a least squares method, etc. Sufficient conditions are provided to ensure that the statistic convergences to a well-known distribution under the null hypothesis (of no change) and diverges to infinity under the alternative; which establishes the consistency of the procedure. Some examples are detailed to illustrate the scope of application of the proposed procedure. Simulation experiments are conducted to illustrate the asymptotic results.
翻译:我们考虑在多变量连续和整数的有价值时间序列中测出变化点,我们建议以一般对比功能的估测符为基础,根据可能性、准相似性、最小平方法等来得出Wald型统计。 提供了充分的条件,以确保统计与在无效假设(不变)下已知分布的趋同性(不变)和在替代假设下对无限性的不同性;这确立了程序的一致性。我们详细列举了一些例子,以说明拟议程序的适用范围。还进行了模拟试验,以说明无孔不入的结果。