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M-procedures for detection of a change under weak dependence

Publication at Faculty of Mathematics and Physics |
2014

Abstract

Procedures detecting a change of regression parameters in a linear model are considered when both the regressors and errors are weakly dependent in the sense of L-p-m-approximability. M-estimators and weighted M-residuals are used to construct test statistics, and their asymptotic distribution is studied under the null hypothesis of no change and under contiguous alternatives.

Estimators of a long-run variance are also considered and studied both analytically and numerically.