Estimating the time of a step change in the multivariate-attribute process mean using ANN and MLE

Amirhossein Amiri, Mohammad Reza Maleki and Fatemeh Sogandi

International Journal of Data Analysis Techniques and Strategies, 2018, vol. 10, issue 1, 81-98

Abstract: In this paper, we consider correlated multivariate-attribute quality characteristics and provide two methods including a modular method based on artificial neural network (ANN) as well as maximum likelihood estimation (MLE) method to estimate the time of change in the parameters of the process mean. We evaluate the performance of the estimators in terms of some criteria in change point estimation and compare them through simulation studies. The results show that the proposed ANN-based model outperforms the MLE approach under most step shifts in the mean vector of the multivariate-attribute process.

Keywords: artificial neural network; ANN; step-change point estimation; multivariate-attribute quality characteristics; maximum likelihood estimation; MLE. (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:10:y:2018:i:1:p:81-98

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