• 제목/요약/키워드: transition probabilities

검색결과 117건 처리시간 0.022초

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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    • 제35권4호
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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.

추이확률의 추정을 위한 확장된 Markov Chain 모형 (An extension of Markov chain models for estimating transition probabilities)

  • 강정혁
    • 경영과학
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    • 제10권2호
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    • pp.27-42
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    • 1993
  • Markov chain models can be used to predict the state of the system in the future. We extend the existing Markov chain models in two ways. For the stationary model, we propose a procedure that obtains the transition probabilities by appling the empirical Bayes method, in which the parameters of the prior distribution in the Bayes estimator are obtained on the collaternal micro data. For non-stationary model, we suggest a procedure that obtains a time-varying transition probabilities as a function of the exogenous variables. To illustrate the effectiveness of our extended models, the models are applied to the macro and micro time-series data generated from actual survey. Our stationary model yields reliable parameter values of the prior distribution. And our non-stationary model can predict the variable transition probabilities effectively.

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계층 전이가 가능한 다계층 대기행렬의 빠른 시뮬레이션 (Fast Simulation of Overflow Probabilities in Multi-Class Queues with Class-Transition)

  • 송미정;배경순;이지연
    • Communications for Statistical Applications and Methods
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    • 제16권2호
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    • pp.217-228
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    • 2009
  • 계층 전이가 가능한 다계층 대기행렬에 대한 빠른 시뮬레이션 방법을 제시하고 이를 이용하여 총 고객의 수가 적정 수준을 초과하는 과부하 발생 확률과 과부하 발생시 각 계층별 평균 고객의 수를 추정한다. 또한 이들 값들이 시스템의 총 로드나 계층별 로드에 따라 어떤 차이를 보이는지도 빠른 시뮬레이션을 통해 서로 비교한다.

Design of Fuzzy IMM Algorithm based on Basis Sub-models and Time-varying Mode Transition Probabilities

  • Kim Hyun-Sik;Chun Seung-Yong
    • International Journal of Control, Automation, and Systems
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    • 제4권5호
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    • pp.559-566
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    • 2006
  • In the real system application, the interacting multiple model (IMM) based algorithm requires less computing resources as well as a good performance with respect to the various target maneuverings. And it further requires an easy design procedure in terms of its structures and parameters. To solve these problems, a fuzzy interacting multiple model (FIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as inputs of a fuzzy decision maker, is proposed. To verify the performance of the proposed algorithm, airborne target tracking is performed. Simulation results show that the FIMM algorithm solves all problems in the real system application of the IMM based algorithm.

Bayesian Analysis of Binary Non-homogeneous Markov Chain with Two Different Time Dependent Structures

  • Sung, Min-Je
    • Management Science and Financial Engineering
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    • 제12권2호
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    • pp.19-35
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    • 2006
  • We use the hierarchical Bayesian approach to describe the transition probabilities of a binary nonhomogeneous Markov chain. The Markov chain is used for describing the transition behavior of emotionally disturbed children in a treatment program. The effects of covariates on transition probabilities are assessed using a logit link function. To describe the time evolution of transition probabilities, we consider two modeling strategies. The first strategy is based on the concept of exchangeabiligy, whereas the second one is based on a first order Markov property. The deviance information criterion (DIC) measure is used to compare models with two different time dependent structures. The inferences are made using the Markov chain Monte Carlo technique. The developed methodology is applied to some real data.

Bayesian Conjugate Analysis for Transition Probabilities of Non-Homogeneous Markov Chain: A Survey

  • Sung, Minje
    • Communications for Statistical Applications and Methods
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    • 제21권2호
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    • pp.135-145
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    • 2014
  • The present study surveys Bayesian modeling structure for inferences about transition probabilities of Markov chain. The motivation of the study came from the data that shows transitional behaviors of emotionally disturbed children undergoing residential treatment program. Dirichlet distribution was used as prior for the multinomial distribution. The analysis with real data was implemented in WinBUGS programming environment. The performance of the model was compared to that of alternative approaches.

Transition Probabilities at Crossing in the Landau-Zener Problem

  • Park, Tae-Jun
    • Bulletin of the Korean Chemical Society
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    • 제26권11호
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    • pp.1735-1737
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    • 2005
  • We obtain probabilities at a crossing of two linearly time-dependent potentials that are constantly coupled to the other by solving a time-dependent Schrödinger equation. We find that the system which was initially localized at one state evolves to split into both states at the crossing. The probability splitting depends on the coupling strength $V_0$ such that the system stays at the initial state in its entirety when $V_0$ = 0 while it is divided equally in both states when $V_0 \rightarrow {\infty}$ . For a finite coupling the probability branching at the crossing is not even and thus a complete probability transfer at $t \rightarrow {\infty}$ is not achieved in the linear potential crossing problem. The Landau-Zener formula for transition probability at $t \rightarrow {\infty}$ is expressed in terms of the probabilities at the crossing.

패널 마코프 체인의 전이확률에 대한 동질성 검정 (Test of homogeneity for transition probabilities in panel Markov chains)

  • 이성덕;조나래
    • 응용통계연구
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    • 제30권1호
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    • pp.147-157
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    • 2017
  • 패널 마코프 체인의 구조를 소개하고 우도함수를 도출하여 전이확률을 추정하였다. 패널 마코프 체인의 전이확률의 동질성 검정통계량으로 LR 통계량을 제안하고 그 극한분포를 제시하였다. 동질성 검정통계량의 극한분포를 패널의 수를 달리하여 모의실험하였으며 패널의 수가 50개 이상인 경우 동질성 검정통계량의 분포가 카이제곱분포를 따르는 것을 확인하였다. 정상적인 경우 검정통계량이 우수한 검정력을 가지는 것을 보였고, 확률보행과정과 같이 비정상적인 경우 검정통계량이 전이확률의 비동질성을 잘 반영하는 것을 확인하였다.

산업인력(産業人力)의 이동(移動)에 관한 추이확률(推移確率) 모형(模型)의 응용(應用) (The Application of Transition Probabilities Models on Estimating the Mobility of Industrial Manpower in Korea)

  • 강정혁
    • 품질경영학회지
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    • 제17권2호
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    • pp.81-92
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    • 1989
  • A class of standard optimization techniques to estimate the stationary transition probabilities among states is discussed. With the use of aggregate time series data on employed labor in industrial sectors, the alternative restricted estimates including minimum absolute deviation, unweighted, weighted, generalized inverse, minimum chi-square and maximum likelihood are evaluated and compared. Analytic and numerical results are shown favorably with the viewpoint of the validity and predictive potentiality of model.

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On Weak Convergence of Some Rescaled Transition Probabilities of a Higher Order Stationary Markov Chain

  • Yun, Seok-Hoon
    • Journal of the Korean Statistical Society
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    • 제25권3호
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    • pp.313-336
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    • 1996
  • In this paper we consider weak convergence of some rescaled transi-tion probabilities of a real-valued, k-th order (k $\geq$ 1) stationary Markov chain. Under the assumption that the joint distribution of K + 1 consecutive variables belongs to the domain of attraction of a multivariate extreme value distribution, the paper gives a sufficient condition for the weak convergence and characterizes the limiting distribution via the multivariate extreme value distribution.

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