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

Author

Listed:
  • Amirhossein Amiri
  • Mohammad Reza Maleki
  • Fatemeh Sogandi

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.

Suggested Citation

  • Amirhossein Amiri & Mohammad Reza Maleki & Fatemeh Sogandi, 2018. "Estimating the time of a step change in the multivariate-attribute process mean using ANN and MLE," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 10(1), pages 81-98.
    • Handle: RePEc:ids:injdan:v:10:y:2018:i:1:p:81-98
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