• Communications for Statistical Applications and Methods
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• 제24권5호
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• pp.507-518
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• 2017

Volatility plays a crucial role in theory and applications of asset pricing, optimal portfolio allocation, and risk management. This paper proposes a combined model of autoregressive moving average (ARFIMA), generalized autoregressive conditional heteroscedasticity (GRACH), and skewed-t error distribution to accommodate important features of volatility data; long memory, heteroscedasticity, and asymmetric error distribution. A fully Bayesian approach is proposed to estimate the parameters of the model simultaneously, which yields parameter estimates satisfying necessary constraints in the model. The approach can be easily implemented using a free and user-friendly software JAGS to generate Markov chain Monte Carlo samples from the joint posterior distribution of the parameters. The method is illustrated by using a daily volatility index from Chicago Board Options Exchange (CBOE). JAGS codes for model specification is provided in the Appendix.

• Water Engineering Research
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• 제4권3호
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• pp.111-126
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• 2003

Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

• Journal of Electrical Engineering and Technology
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• 제6권1호
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• pp.25-31
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• 2011

The purpose of power system maintenance is to prevent equipment failure. The maintenance strategy should be designed to balance costs and benefits because frequent maintenance increases cost while infrequent maintenance can also be costly due to electricity outages. This paper proposes maintenance modeling of a power distribution system using reliability centered maintenance (RCM). The proposed method includes comprehensive equipment modeling and impact analysis to evaluate the effect of equipment faults. The problem of finding the optimum maintenance strategy is formulated in terms of dynamic programming. The applied power system is based on the RBTS Bus 2 model, and the results demonstrate the potential for designing a maintenance strategy using the proposed model.

• 제어로봇시스템학회논문지
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• 제8권4호
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• pp.288-291
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• 2002

We characterize multipath fading channel dynamics at the packet level and analyze the corresponding data queueing performance in various environments. We identify the similarity between wire-line queueing analysis and wireless network per-formance analysis. The second order channel statistics, i.e. channel power spectrum, is fecund to play an important role in the modeling of multipath fading channels. However, it is identified that the first order statistics, i.e. channel CDF also has significant impact on queueing performance. We use a special Markov chain, so-called CMPP, throughout this paper.

• 품질경영학회지
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• 제32권4호
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• pp.156-168
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• 2004

This research investigates the statistical efficiency of variable sampling size & sampling interval(VSSI) $\bar{X}$ charts under two assignable causes. Algorithms for calculating the average run length(ARL) and average time to signal(ATS) of the VSSI $\bar{X}$ chart are proposed by employing Markov chain method. States of the process are defined according to the process characteristics after the occurrence of an assignable cause. Transition probabilities are carefully derived from the state definition. Statistical properties of the proposed chart are also investigated. A simple procedure for designing the proposed chart is presented based on the properties. Extensive sensitivity analyses show that the VSSI $\bar{X}$ chart is superior to the VSS or VSI $\bar{X}$ chart as well as to the Shewhart $\bar{X}$ chart in statistical sense, even tinder two assignable causes.

• 한국경영과학회지
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• 제30권4호
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• pp.1-14
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• 2005

We propose a VSSI-CRL(Variable Sampling Size and Samplina Interval-Conforming Run length) synthetic control chart in order to improve the statistical characteristics of both the VSSI chart and the CRL synthetic chart. The VSSI-CRL chart utilizes VSSI sampling scheme, but it produces a signal only when the CRI is less than a given limit. An algorithm for calculating the ARL(Average Run length) and ATS(Average Time to Signal) of the VSSI-CRL chart is developed by employing Markov chain method. We present some lemmas for describing the statistical characteristics of the VSSI-CRL chart under in-control state. A procedure for designing the VSSI-CRL chart is proposed based on the lemmas. Extensive comparative studios show that the VSSI-CRL chart is superior to the CRL synthetic chart or the VSSI chart in general, and is comparable to the EWMA chart in ATS performance.

• Computers and Concrete
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• 제18권1호
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• pp.69-97
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• 2016

Performance-based remaining life assessment of reinforced concrete bridge girders, subject to chloride-induced corrosion of reinforcement, is addressed in this paper. Towards this, a methodology that takes into consideration the human judgmental aspects in expert decision making regarding condition state assessment is proposed. The condition of the bridge girder is specified by the assignment of a condition state from a set of predefined condition states, considering both serviceability- and ultimate- limit states, and, the performance of the bridge girder is described using performability measure. A non-homogeneous Markov chain is used for modelling the stochastic evolution of condition state of the bridge girder with time. The thinking process of the expert in condition state assessment is modelled within a probabilistic framework using Brunswikian theory and probabilistic mental models. The remaining life is determined as the time over which the performance of the girder is above the required performance level. The usefulness of the methodology is illustrated through the remaining life assessment of a reinforced concrete T-beam bridge girder.

• 한국경영과학회지
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• 제32권1호
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• pp.147-160
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• 2007

In this paper, the optimal decision making strategy for resource management is viewed in terms of a combined strategy of planting and producing time. A model which can be used to determine the optimal management strategy is developed, and focuses on how to design the operation of a Markov chain so as to optimize its performance. This study estimated a dynamic stochastic model to compare alternative production style and used the net present value of returns to evaluate the scenarios. The managers in this study may be able to increase economic returns by delaying produce in order to market larder, more valuable commodities.

• 한국국방경영분석학회지
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• 제17권1호
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• pp.1-24
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• 1991

This report concerns the study of deciding replacement requirements for 1/4ton truck in Korea. Two causes of replacement, accidental loss and wearout are considered in the replacement requirements model which was developed in Defence Logistics Agency. The model represents the state of 1/4 ton truck inventory over time as a finite Markov chain process. An accidental loss rate, yearly usage rates. wearout rates are used in conjuction with the current mileage distribution of the inventory to forecast replacement requirements in future time periods.

• Asian-Australasian Journal of Animal Sciences
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• 제13권3호
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.