Off-line detection of multiple change points with the Filtered Derivative with p-Value method

Details Off-line detection of multiple change points with the Filtered Derivative with p-Value method Off-line detection of multiple change points with the Filtered Derivative with p-Value method

2010-03-22

arxiv.org/abs/1003.4148v2

Sequential Analysis (2010) 26

Mathematics

Statistics Theory

Scientific paper

This paper deals with off-line detection of change points for time series of independent observations, when the number of change points is unknown. We propose a sequential analysis like method with linear time and memory complexity. Our method is based at first step, on Filtered Derivative method which detects the right change points but also false ones. We improve Filtered Derivative method by adding a second step in which we compute the p-values associated to each potential change points. Then we eliminate as false alarms the points which have p-value smaller than a given critical level. Next, our method is compared with the Penalized Least Square Criterion procedure on simulated data sets. Eventually, we apply Filtered Derivative with p-Value method to segmentation of heartbeat time series, and detection of change points in the average daily volume of financial time series.

Affiliated with

Also associated with

No associations

Rating

Off-line detection of multiple change points with the Filtered Derivative with p-Value method does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Off-line detection of multiple change points with the Filtered Derivative with p-Value method, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Off-line detection of multiple change points with the Filtered Derivative with p-Value method will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-206467