ENBIS Spring Meeting 2018

4 – 6 June 2018; Florence, Italy Abstract submission: 17 November 2017 – 20 April 2018

Statistical monitoring of nonlinear profiles using mixed effects models

5 June 2018, 09:25 – 09:50

Abstract

Submitted by
Arda Vanli
Authors
Arda Vanli (Florida State University, Department of Industrial and Manufacturing Engineering)
Abstract
In this research we propose a profile monitoring method for sequential monitoring of dose-response curves. Dose-response curve experiments are commonly utilized in agricultural and food production applications. In most of the profile monitoring approaches, it is assumed that the errors are independent and identically distributed random variables. In many practical profile monitoring problems, however, the errors are autocorrelated. In this research we study the effectiveness of mixed-effects models to account for autocorrelation within profiles. We consider a Phase II study and investigate the effectiveness of both parametric and nonparametric regression models in monitoring nonlinear profiles. The application of the method is illustrated on a replicated dose-response experiment.

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