Detecting changes in a data stream is an important area of research with many applications. In this paper, we present novel methods for the detection and estimation of change. In contrast to previously proposed tools, our techniques provide proven guarantees on the statistical significance of detected change. In addition to providing reliable detection of change, our method allows for a meaningful description and quantification of those changes. Our techniques are nonparametric and so they require no prior assumptions on the nature of the distribution that generates the data, except for assuming that points in the stream are generated independently. Additionally, these techniques work for both continuous and discrete data. In an experimental study we demonstrate the usefulness of our techniques.
Kifer et al. REF present a method for the detection and estimation of change in data streams.
Detecting Change in Data Streams
VLDB
Computer Science