• 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.

• 한국정보통신학회논문지
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• 제26권2호
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• pp.317-320
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• 2022

This paper studies real-time error in the context of monitoring a symmetric binary information source over a delay system. To obtain the average real-time error, the delay system is modeled and analyzed as a discrete time Markov chain with a finite state space. Numerical analysis is performed on various system parameters such as state transition probabilities of information source, transmission times, and transmission frequencies. Given state transition probabilities and transmission times, we investigate the relationship between the transmission frequency and the average real-time error. The results can be used to investigate the relationship between real-time errors and age of information.

• 한국정보통신학회논문지
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• 제27권1호
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• pp.135-138
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• 2023

In this paper, we study real-time error in the context of monitoring a binary information source through a delay system. To derive the average real-time error, we model the delay system as a discrete time Geo/D/1/1 queueing model. Using a discrete time three-dimensional Markov chain with finite state space, we analyze the queueing model. We also perform some numerical analysis on various system parameters: state transition probabilities of binary information source; transmission times; and transmission frequencies. When the state changes of the information source are positively correlated and negatively correlated, we investigate the relationship between transmission time and transmission frequency.

• 응용통계연구
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• 제33권1호
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• pp.47-59
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• 2020

본 논문에서는 마코프 이항 회귀 모형의 시차가 알려져 있거나 그렇지 않은 경우일 때, t-링크 함수를 갖는 종단적 마코프 이항 회귀 모형을 제시한다. 일반적으로, 이항 회귀 모형에서는 로직 모형이나 프로빗 모형이 주로 사용된다. t-링크 함수는 t 분포가 자유도가 커질수록 정규분포로 근사하기 때문에 프로빗 모형을 대신 더 많은 유연성을 위해 사용될 수 있다. 게다가 마코프 회귀모형은 종단 자료에 대해 사용될 수 있다. 우리는 마코프 회귀 모형의 시차를 결정하기 위해 베이지안 방법을 제시하고자 한다. 특히, 각 모델의 차수에 대해 알고 있는 경우에는 DIC를 기준으로 모델 비교를 실시하였다. 모델의 차수에 대해 모르는 경우에는 가능한 모델들의 사후 확률을 이용하였다. 복잡한 베이지안 계산을 해결하기 위하여 Albert와 Chib (1993), Kuo와 Mallick (1998)과 Erkanli 등 (2001)의 방법을 이용하여 모델을 재설정하였다. 제안하는 방법은 시뮬레이션 데이터와 Somer 등 (1984)에 의해 조사된 인도네시아 어린이 종단 데이터에 적용했다. 마코프 이항 회귀모형의 순서에 대해서 아는 경우와 모르는 경우를 각각 가정하여 최적의 모델을 알아보기 위해 MCMC 방법을 사용하였다. 또한, 매트로폴리스 해스팅 알고리즘의 수렴성을 점검하기 위해 Gelman과 Rubin의 진단을 이용했다.

• 천문학회보
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• 제45권1호
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• pp.51.3-52
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• 2020

We present the status of the development of a Markov Chain Monte Carlo (MCMC) parameter estimation (PE) pipeline for compact binary coalescences (CBCs) with the Japanese KAGRA gravitational-wave (GW) detector. The pipeline is included in the KAGRA Algorithm Library (KAGALI). Basic functionalities are benchmarked from the LIGO Algorithm Library (LALSuite) but the KAGRA MCMC PE pipeline will provide a simpler, memory-efficient pipeline to estimate physical parameters from gravitational waves emitted from compact binaries consisting of black holes or neutron stars. Applying inspiral-merge-ringdown and inspiral waveforms, we performed simulations of various black hole binaries, we performed the code sanity check and performance test. In this talk, we present the situation of GW observation with the Covid-19 pandemic. In addition to preliminary PE results with the KAGALI MCMC PE pipeline, we discuss how we can optimize a CBC PE pipeline toward the next observation run.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.1-9
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• 2007

A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4825-4847
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• 2016

In this paper, we focus on the per-flow throughput analysis of IEEE 802.11 multi-hop ad hoc networks. The importance of an accurate saturation throughput model lies in establishing the theoretical foundation for effective protocol performance improvements. We argue that the challenge in modeling the per-flow throughput in IEEE 802.11 multi-hop ad hoc networks lies in the analysis of the freezing process and probability of collisions. We first classify collisions occurring in the whole transmission process into instantaneous collisions and persistent collisions. Then we present a four-dimensional Markov chain model based on the notion of the fixed length channel slot to model the Binary Exponential Backoff (BEB) algorithm performed by a tagged node. We further adopt a continuous time Markov model to analyze the freezing process. Through an iterative way, we derive the per-flow throughput of the network. Finally, we validate the accuracy of our model by comparing the analytical results with that obtained by simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3446-3464
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• 2017

Backoff mechanism serves as one of the key technologies in the MAC-layer of wireless mobile networks. The traditional Binary Exponential Backoff (BEB) mechanism in IEEE 802.11 Distributed Coordination Function (DCF) and other existing backoff mechanisms poses several performance issues. For instance, the Contention Window (CW) oscillations occur frequently; a low delay QoS guarantee cannot be provided for real-time transmission, and services with different priorities are not differentiated. For these problems, we present a novel Multi-Priority service differentiated and Adaptive Backoff (MPAB) algorithm over IEEE 802.11 DCF for wireless mobile networks in this paper. In this algorithm, the backoff stage is chosen adaptively according to the channel status and traffic priority, and the forwarding and receding transition probability between the adjacent backoff stages for different priority traffic can be controlled and adjusted for demands at any time. We further employ the 2-dimensional Markov chain model to analyze the algorithm, and derive the analytical expressions of the saturation throughput and average medium access delay. Both the accuracy of the expressions and the algorithm performance are verified through simulations. The results show that the performance of the MPAB algorithm can offer a higher throughput and lower delay than the BEB algorithm.

• 한국통신학회논문지
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• 제19권5호
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• pp.805-814
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• 1994

본 논문에서는 실패상태와 성공상태를 포함시키는 보조 Markov 천이행렬을 이용하여 패킷무선망의 성능을 구할 수 있는 새로운 분석방식을 제시하고 패킷오류 발생이 송신 PRU의 수 X와 수신 PRU의 수 R로 이루어지는 망상태(X, R)의 변화에 미치는 영향을 고려한다. 패킷무선망은 연속시간 Markov 체인 모델 그리고 무선채널은 경판정 Viterbi복호기와 비트변환확산부호계열을 이용한 DS/BPSK CDMA에 대하여 검토한다. 슬롯되지 않은 분산된 다중도약 패킷무선망에서 무선채널의 채널심볼오류가 패킷오류 발생에 미치는 진행과정은 Poisson 분포 그리고 오류발생시간을 지수분포로 가정한다. 신호대 잡음비와 심볼당 확산부호계열의 칩수와 같은 무선채널의 매개변수와 PRU의 수와 허용된 트래픽율과 같은 망의 매개변수를 갖는 함수로 망처리량을 구함으로써 Markov 패킷무선망과 부호화된 DS/BPSK 무선채널을 결합하여 종합적으로 분석할 수 있음을 보인다.

• Journal of the Korean Data and Information Science Society
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• 제25권1호
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.