On-line detection of continuous changes in stochastic processes

This paper addresses the issue of detecting changes in stochastic processes. In conventional studies on change detection, it has been explored how to detect discrete changes for which the statistical models of data suddenly change. We are rather concerned with how to detect continuous changes which occurs incrementally over some successive periods. This paper gives a novel methodology for detecting continuous changes. We first define the information-theoretic measure of continuous change and prove that it is invariant with respect to the parametrization of statistical model. We then propose an efficient algorithm to detect continuous changes according to the proposed measure. We demonstrate the effectiveness of our method through the experiments using synthetic data and the applications to security and economic event detection.