• Title/Summary/Keyword: Markov Chain Process

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A Markov Chain Representation of Statistical Process Monitoring Procedure under an ARIMA(0,1,1) Model (ARIMA(0,1,1)모형에서 통계적 공정탐색절차의 MARKOV연쇄 표현)

  • 박창순
    • The Korean Journal of Applied Statistics
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    • v.16 no.1
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    • pp.71-85
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    • 2003
  • In the economic design of the process control procedure, where quality is measured at certain time intervals, its properties are difficult to derive due to the discreteness of the measurement intervals. In this paper a Markov chain representation of the process monitoring procedure is developed and used to derive its properties when the process follows an ARIMA(0,1,1) model, which is designed to describe the effect of the noise and the special cause in the process cycle. The properties of the Markov chain depend on the transition matrix, which is determined by the control procedure and the process distribution. The derived representation of the Markov chain can be adapted to most different types of control procedures and different kinds of process distributions by obtaining the corresponding transition matrix.

A Repair Process with Embedded Markov Chain

  • Lee, Eui-Yong;Munsup Seoh
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.515-522
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    • 1999
  • A repair process of a system consisting of both perfect repairs and minimal repairs is introduced. The type of repair, when the system fails, is determined by an embedded two state Markov chain. We study several stochastic properties of the process including the preservation of ageing properties and the monotonicities of the time between successive repairs. After assigning repair costs to the process, we also show that an optimal repair policy uniquely exists, if the underlying life distribution of the system has DMRL.

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Performance Evaluation of the WiMAX Network Based on Combining the 2D Markov Chain and MMPP Traffic Model

  • Saha, Tonmoy;Shufean, Md. Abu;Alam, Mahbubul;Islam, Md. Imdadul
    • Journal of Information Processing Systems
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    • v.7 no.4
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    • pp.653-678
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    • 2011
  • WiMAX is intended for fourth generation wireless mobile communications where a group of users are provided with a connection and a fixed length queue. In present literature traffic of such network is analyzed based on the generator matrix of the Markov Arrival Process (MAP). In this paper a simple analytical technique of the two dimensional Markov chain is used to obtain the trajectory of the congestion of the network as a function of a traffic parameter. Finally, a two state phase dependent arrival process is considered to evaluate probability states. The entire analysis is kept independent of modulation and coding schemes.

CHAIN DEPENDENCE AND STATIONARITY TEST FOR TRANSITION PROBABILITIES OF MARKOV CHAIN UNDER LOGISTIC REGRESSION MODEL

  • Sinha Narayan Chandra;Islam M. Ataharul;Ahmed Kazi Saleh
    • Journal of the Korean Statistical Society
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    • v.35 no.4
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    • pp.355-376
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    • 2006
  • To identify whether the sequence of observations follows a chain dependent process and whether the chain dependent or repeated observations follow stationary process or not, alternative procedures are suggested in this paper. These test procedures are formulated on the basis of logistic regression model under the likelihood ratio test criterion and applied to the daily rainfall occurrence data of Bangladesh for selected stations. These test procedures indicate that the daily rainfall occurrences follow a chain dependent process, and the different types of transition probabilities and overall transition probabilities of Markov chain for the occurrences of rainfall follow a stationary process in the Mymensingh and Rajshahi areas, and non-stationary process in the Chittagong, Faridpur and Satkhira areas.

Implementation of Markov Chain: Review and New Application (관리도에서 Markov연쇄의 적용: 복습 및 새로운 응용)

  • Park, Chang-Soon
    • The Korean Journal of Applied Statistics
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    • v.24 no.4
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    • pp.657-676
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    • 2011
  • Properties of statistical process control procedures may not be derived analytically in many cases; however, the application of a Markov chain can solve such problems. This article shows how to derive the properties of the process control procedures using the generated Markov chains when the control statistic satisfies the Markov property. Markov chain approaches that appear in the literature (such as the statistical design and economic design of the control chart as well as the variable sampling rate design) are reviewed along with the introduction of research results for application to a new control procedure and reset chart. The joint application of a Markov chain approach and analytical solutions (when available) can guarantee the correct derivation of the properties. A Markov chain approach is recommended over simulation studies due to its precise derivation of properties and short calculation times.

Implementation of Markov chain: Review and new application (관리도에서 Markov연쇄의 적용: 복습 및 새로운 응용)

  • Park, Changsoon
    • The Korean Journal of Applied Statistics
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    • v.34 no.4
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    • pp.537-556
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    • 2021
  • Properties of statistical process control procedures may not be derived analytically in many cases; however, the application of a Markov chain can solve such problems. This article shows how to derive the properties of the process control procedures using the generated Markov chains when the control statistic satisfies the Markov property. Markov chain approaches that appear in the literature (such as the statistical design and economic design of the control chart as well as the variable sampling rate design) are reviewed along with the introduction of research results for application to a new control procedure and reset chart. The joint application of a Markov chain approach and analytical solutions (when available) can guarantee the correct derivation of the properties. A Markov chain approach is recommended over simulation studies due to its precise derivation of properties and short calculation times.

A Study on the Fatigue Reliability of Structures by Markov Chain Model (Markov Chain Model을 이용한 구조물의 피로 신뢰성 해석에 관한 연구)

  • Y.S. Yang;J.H. Yoon
    • Journal of the Society of Naval Architects of Korea
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    • v.28 no.2
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    • pp.228-240
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    • 1991
  • Many experimental data of fatigue crack propagation show that the fatigue crack propagation process is stochastic. Therefore, the study on the crack propagation must be based on the probabilistic approach. In the present paper, fatigue crack propagation process is assumed to be a discrete Markov process and the method is developed, which can evaluate the reliability of the structural component by using Markov chain model(Unit step B-model) suggested by Bogdanoff. In this method, leak failure, plastic collapse and brittle fracture of the critical component are taken as failure modes, and the effects of initial crack distribution, periodic and non-periodic inspection on the probability of failure are considered. In this method, an equivalent load value for random loading such as wave load is used to facilitate the analysis. Finally some calculations are carried out in order to show the usefulness and the applicability of this method. And then some remarks on this method are mentioned.

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Reliability Analysis of Multi-Component System Considering Preventive Maintenance: Application of Markov Chain Model (예방정비를 고려한 복수 부품 시스템의 신뢰성 분석: 마코프 체인 모형의 응용)

  • Kim, Hun Gil;Kim, Woo-Sung
    • Journal of Applied Reliability
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    • v.16 no.4
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    • pp.313-322
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    • 2016
  • Purpose: We introduce ways to employ Markov chain model to evaluate the effect of preventive maintenance process. While the preventive maintenance process decreases the failure rate of each subsystems, it increases the downtime of the system because the system can not work during the maintenance process. The goal of this paper is to introduce ways to analyze this trade-off. Methods: Markov chain models are employed. We derive the availability of the system consisting of N repairable subsystems by the methods under various maintenance policies. Results: To validate our methods, we apply our models to the real maintenance data reports of military truck. The error between the model and the data was about 1%. Conclusion: The models developed in this paper fit real data well. These techniques can be applied to calculate the availability under various preventive maintenance policies.

Sensitivity of Conditions for Lumping Finite Markov Chains

  • Suh, Moon-Taek
    • Journal of the military operations research society of Korea
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    • v.11 no.1
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    • pp.111-129
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    • 1985
  • Markov chains with large transition probability matrices occur in many applications such as manpowr models. Under certain conditions the state space of a stationary discrete parameter finite Markov chain may be partitioned into subsets, each of which may be treated as a single state of a smaller chain that retains the Markov property. Such a chain is said to be 'lumpable' and the resulting lumped chain is a special case of more general functions of Markov chains. There are several reasons why one might wish to lump. First, there may be analytical benefits, including relative simplicity of the reduced model and development of a new model which inherits known or assumed strong properties of the original model (the Markov property). Second, there may be statistical benefits, such as increased robustness of the smaller chain as well as improved estimates of transition probabilities. Finally, the identification of lumps may provide new insights about the process under investigation.

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