This paper is concerned with persistent system identification for plants that are equipped with binary sensors whose unknown parameter is a random process represented by a Markov chain. We treat two classes of problems. In the first class, the parameter is a stochastic process modeled by an irreducible and aperiodic Markov chain with transition rates sufficiently faster than adaptation rates of...

This paper investigates control charts for detecting special causes in an ARIMA(0,1,1) process that is being adjusted automatically after each observation using a minimum mean-squared error adjustment policy. It is assumed that the adjustment mechanism is designed to compensate for the inherent variation due to the ARIMA(0,1,1) process, but it is desirable to detect and eliminate special causes...

Statistical process control charts are intended to assist operators of a usually stable system in monitoring whether a change has occurred in the process. When a change does occur, the control chart should detect it quickly. If the operator can also be provided information that aids in the search for the special cause, then critical off-line time can be saved. We investigate a process-monitorin...

This paper presents the analysis of a finite buffer renewal input queue wherein the customers can decide either to join the queue with a probability or to balk. The service process is Markovian service process (MSP ) governed by an underlyingm-state Markov chain. Employing the supplementary variable and embedded Markov chain techniques, the steadystate system length distributions at pre-arrival...

In this study we model the daily rainfall occurrence using Markov Chain Analogue Yearmodel (MCAYM) and the intensity or amount of daily rainfall using three different probability distributions; gamma, exponential and mixed exponential distributions. Combining the occurrence and intensity model we obtain Markov Chain Analogue Year gamma model (MCAYGM), Markov Chain Analogue Year exponentia...

In this paper, we develop a process control approach to detect linear trends in the process mean. A statistic based on the deviation between the target mean and the expected mean of the process is used in the development of the new approach. The statistic is shown to have a Chi-square distribution. The approach is described and its performance is compared with Cumulative Sum (CUSUM), Exponentia...

this paper is devoted to the study of determining optimal process mean in system production with the two markets for the sale of goods. in this paper, we developed an absorbing markov chain model in production systems where all items are inspected %100 for conformance with their specification limits. when the value of the quality characteristic of an item falls below a lower limit, the item is ...

ABSTRACT Head start values — that is, non-zero initial values for the summary statistics of Markovtype control schemes such as the well known CUSUM schemes — are throughly recommended in the literature and used by quality control practitioners. The rationale of it is as follows: if the process is operating in-control, the summary statistic of the control scheme is soon brought to zero, so that ...

Conditional Markov chain models of observed aggregate share–type data have been used by economic researchers for several years, but the classes of models commonly used in practice are often criticized as being purely ad hoc because they are not derived from micro–behavioral foundations. The primary purpose of this paper is to show that the estimating equations commonly used to estimate these co...