Nonlinear profile monitoring with single index models

Abstract

Abstract We consider change‐point detection and estimation in sequences of functional observations. This setting often arises when the quality of a process is characterized by such observations, called profiles, and monitoring profiles for changes in structure can be used to ensure the stability of the process over time. We propose a nonparametric approach using a single index model (SIM), where instead of monitoring the profile itself for a change, we monitor an ‐based statistic on the coefficients generated by the SIM. Through simulation we show our novel method outperforms existing multivariate profile monitoring methods.

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