Monotonic change point estimation of generalized linear model-based regression profiles

In this paper a Maximum Likelihood Estimator is derived in the Generalized Linear Model-based regression profiles under the monotonic change in Phase II. The performance of proposed estimator is comprehensively investigated through some special cases and compared to estimators under step change and drift. The results show that the proposed estimator has better performance in small and medium shifts under different increasing changes. Finally, the applicability of the proposed estimator is illustrated using a real case.