• Korean Journal of Biological Psychiatry
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• v.4 no.2
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• pp.194-197
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• 1997

Neural network models, also known as connectionist models or PDP models, simulate some functions of the brain and may promise to give insight in understanding the cognitive brain functions. The models composed of neuron-like elements that are linked into circuits can learn and adapt to its environment in a trial and error fashion. In this article, the history and principles of the neural network modeling are briefly reviewed, and its applications to psychiatry are discussed.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.185-192
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• 2009

The research contributes extending and reviewing of restricted (constrained) and unrestricted (unconstrained) models in GLM(Generalized Linear Models). The paper includes the methodology for finding EMS(Expected Mean Square) and $F_0$ ratio. The results can be applied to the gauge R&R(Reproducibility and Repeatability) in MSA(Measurement System Analysis).

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.119-130
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• 1989

This paper presents average travel time models automated warehousing system where the stacker crane transports only one pallet at a time with the tchebychev travel, I/O point is located at the cornor of the rack, and items are stored by the class-based storage assignment rule. In this study, the racks are treated as the continuous rectangle in time and a statistical approach was used to develop the models. In order to test the proposed models, average travel times determined by the models are compared with the true values for various rack shapes.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.895-903
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• 2009

The penalized partial likelihood based on restricted maximum likelihood method has been widely used for the inference of frailty models. However, the standard-error estimate for frailty parameter estimator can be downwardly biased. In this paper we show that such underestimation can be corrected by using hierarchical likelihood. In particular, the hierarchical likelihood gives a statistically efficient procedure for various random-effect models including frailty models. The proposed method is illustrated via a numerical example and simulation study. The simulation results demonstrate that the corrected standard-error estimate largely improves such bias.

• MALSORI
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• no.67
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• pp.79-102
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• 2008

In this paper, we investigate the relation between Bayes factor and likelihood ratio test (LRT) approaches and apply the neighborhood information of Bayes factor to building an alternate hypothesis model of the LRT system. To consider the neighborhood approaches, we contemplate a distance measure between models and algorithms to be applied. We also evaluate several methods to improve performance of utterance verification using neighborhood information. Among these methods, the system which adopts anti-models built by collecting mixtures of neighborhood models obtains maximum error rate reduction of 17% compared to the baseline, linear and weighted combination of neighborhood models.

• Journal of Korean Society for Quality Management
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• v.25 no.1
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• pp.44-55
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• 1997

In order to determine procedures for a, pp.opriate model selection of technological growth curves, numerous time series that were representative of growth behavior were collected according to data characteristics. Three different growth curve models were fitted onto data sets in an attempt to determine which growth curve models achieved the best forecasts for types of growth data. The analysis of the results gives rise to an a, pp.oach for selecting a, pp.opriate growth curve models for a given set of data, prior to fitting the models, based on the characteristics of the goodness of fit test.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.43-48
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• 2005

We consider the problem of testing for parameter changes in time series models based on a cusum test. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case has not been discussed in the literature. Therefore, here we develop a cusum test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model and that of the autocovariances of a linear process. We also consider the variance change test for unstable models with unit roots and GARCH models.

• Journal of the Korea Society for Simulation
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• v.6 no.1
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• pp.1-13
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• 1997

In this paper, we present a partitioning algorithm for distributed simulation of DEVS (Discrete Event System Specification) models. To preserve concurrency inherent in models, the proposed algorithm utilizes the structural information of models. Through benchmark simulation experiments, we show that the proposed algorithm can generate good partitions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.127-136
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• 1998

In many cases where the binomial distribution fails to apply to real world data it is because of more variability in the data than can be explained by that distribution. Several authers have proposed models that are useful in explaining extra-binomial variation. In this paper we point out a characterization of sequences of exchangeable Bernoulli variables which can be used to develop models which show more variability than the binomial. We give sufficient conditions which will yield such models and show how existing models can be continued to generate further models. A numerical example and simulation given.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.917-923
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• 2012

We perform a comparison of time series models that include seasonal ARIMA, Fractional ARIMA, and Holt-Winters models; in addition, we also consider hourly and daily air passenger data. The results of the performance evaluation of the models show that the Holt-Winters methods outperforms other models in terms of MAPE.