Inference for post-change parameters after sequential CUSUM test under AR(1) model

摘要

For a sequence of correlated normal random variables following the AR(1) change-point model, the inference problem for the change-point and post-change mean is considered when the residuals are used to form the sequential model-based CUSUM procedure. Higher order biases and corrected pivots are developed to construct confidence intervals. Numerical comparison with the classical CUSUM procedure shows that the model-based CUSUM procedure has smaller average delay detection time and change-point estimation bias. Northern hemisphere average temperature data is used for illustration. (C) 2015 Elsevier B.V. All rights reserved.