Real time change-point detection in a nonlinear quantile model

Sequential change point detection in linear quantile regression models

We develop a method for sequential detection of structural changes in linear quantile regression models. We establish the asymptotic properties of the proposed test statistic, and demonstrate the advantages of the proposed method over existing tests through simulation. © 2015 Elsevier B.V. All rights reserved.

Real-time financial surveillance via quickest change-point detection methods

A Real-Time Image Change Detection System

Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This p...

A Real-Time Image Change Detection System

Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This p...

Empirical likelihood test in a posteriori change-point nonlinear model

In this paper, in order to test whether changes have occurred in a nonlinear parametric regression, we propose a nonparametric method based on the empirical likelihood. Firstly, we test the null hypothesis of no-change against the alternative of one change in the regression parameters. The asymptotic behaviour of the empirical likelihood statistic under the null hypothesis and its alternative i...