Filtered derivative with p-value method for multiple change-points detection

Pierre R., Bertrand (1) , Mehdi Fhima (2)

1 APIS - Analysis of irregular Processes, Images and Signal,applications in biology and medicine
2 LMBP - Laboratoire de Mathématiques Blaise Pascal

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.

Mots clés: Off-line detection of multiple change points; Filtered Derivative method; p-values; linear time and memory complexity.; linear time and memory complexity

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Pierre R., Bertrand, Mehdi Fhima. Filtered derivative with p-value method for multiple change-points detection. International Workshop in Sequential Methodologies, Jun 2009, Troyes, France. pp.6. ⟨hal-00461215⟩