A Clustering Approach for Change Point Estimation in Multivariate Normal Processes
نویسندگان
چکیده
Control charts are the most popular monitoring tools used to distinguish between special (assignable) and common causes of variation and to detect any changes in processes. The time that a control chart gives an out of control signal is not the real time of change. The actual time of the change is called the change point. Knowing the real time of the change will help and simplify finding the assignable causes of the signal which may be the result of a shift in the process mean or change in process variability. In this paper we propose a simple change point estimator based on clustering approach for estimating the time of a step change in a multivariate process when the observations follow a multivariate normal distribution. The performance of the proposed estimator is assessed through computer simulations. The results show that our proposed estimator performs as effective as the existing maximum likelihood estimator proposed by Nedumaran and Pignatiello [1].
منابع مشابه
A Novel Clustering Approach for Estimating the Time of Step Changes in Shewhart Control Charts
Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel app...
متن کاملStep change point estimation in the multivariate-attribute process variability using artificial neural networks and maximum likelihood estimation
In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...
متن کاملA robust wavelet based profile monitoring and change point detection using S-estimator and clustering
Some quality characteristics are well defined when treated as response variables and are related to some independent variables. This relationship is called a profile. Parametric models, such as linear models, may be used to model profiles. However, in practical applications due to the complexity of many processes it is not usually possible to model a process using parametric models.In these cas...
متن کاملDrift Change Point Estimation in the rate and dependence Parameters of Autocorrelated Poisson Count Processes Using MLE Approach: An Application to IP Counts Data
Change point estimation in the area of statistical process control has received considerable attentions in the recent decades because it helps process engineer to identify and remove assignable causes as quickly as possible. On the other hand, improving in measurement systems and data storage, lead to taking observations very close to each other in time and as a result increasing autocorrelatio...
متن کاملImproving the Performance of Bayesian Estimation Methods in Estimations of Shift Point and Comparison with MLE Approach
A Bayesian analysis is used to detect a change-point in a sequence of independent random variables from exponential distributions. In This paper, we try to estimate change point which occurs in any sequence of independent exponential observations. The Bayes estimators are derived for change point, the rate of exponential distribution before shift and the rate of exponential distribution after s...
متن کامل