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Detecting and Estimating the Time of Single Step Change in Nonlinear Profiles

Ghazizadeh Ahsaei, Ali | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 45069 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Mahlooji, Hashem
  7. Abstract:
  8. This effort attempts to study the change point problem in the area of non-linear profiles. Two methods for estimating the time of a single step change is proposed. In the first method a model consisting of two networks which is based on artificial neural networks is proposed. These networks are different only in their training data. One network is trained for ascending segments of the profile and the other is trained for descending segments of the profile. In the second method the maximum likelihood estimator (MLE) of the single step change is analyzed. Due to the complexity of estimating the parameters of the non-linear model by MLE, this estimator is based on the difference between the response variables and in-control profile curve. The likelihood function (or its logarithm) is complicated enough to prevent one to estimate the time of change by an exact method. So we resort to techniques in numerical methods. The merits of the proposed estimators are evaluated through simulation experiments. The results show that the estimators provide accurate and rather precise estimates of the single step change point in non-linear profiles in the selected case problems
  9. Keywords:
  10. Statistical Quality Control ; Artificial Neural Network ; Nonlinear Profile ; Step Change Point ; Multi-Layer Perceptron (MLP) ; Maximum Likelihood Estimation

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