• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.339-345
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• 2004

This paper deals with a mixed logit model for ordered polytomous data. There are two types of factors affecting the response varable in this paper. One is a fixed factor with finite quantitative levels and the other is a random factor coming from an experimental structure such as a randomized complete block design. It is discussed how to set up the model for analyzing ordered polytomous data and illustrated how to estimate the paramers in the given model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.909-915
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• 2006

To predict autogenous shrinkage of concrete, unsaturated pore compensation factor could be calculated by experiments of autogenous shrinkage of cement paste on the assumption that the differences between degree of hydration and strain rate of autogenous shrinkage are unsaturated pore formation rate. Applying unsaturated pore compensation factor on modified Pickket model considering contribution factor and non-contribution factor to autogenous shrinkage of concrete, experimental data and existing model were compared. From the results modified Pickket model was verified to present similar tendency between Tazawa model and experimental data, but CEB-FIP model might be corrected because this model uses ultimate autogenous shrinkage underestimated and the same autogenous time function of concrete material properties considering only compressive strength.

• Journal of the Korean Statistical Society
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• v.35 no.3
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• pp.261-280
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• 2006

We have developed a new model selection criteria, the partial intrinsic Bayes factor, which is designed for cases when we select a model among a small number of candidate models. For example, we can choose only a few candidate models after exploring scatter plots. By simulation study, we have showed that PIBF performs better than AIC, BIC and GCV.

• Korean Journal of Child Studies
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• v.19 no.2
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• pp.97-113
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• 1998

The purpose of this paper was to evaluate hypothesized alternative models for the factor structure of the Korean Version of the Aberrant Behavior Checklist(K-ABC) using standardized samples. Confirmatory factor analyses of correlated factor models using the Jeroskog method were carried out. Analyses supported the two-factor processing model. When the achievement scale was added, a three factor model (two processing factors and an achievement factor) emerged. When factorially uncorrelated models were analyzed, fit indices proved to be improper.

• East Asian mathematical journal
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• v.34 no.1
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• pp.1-16
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• 2018

We study an optimization problem for hyperbolic absolute risk aversion (HARA) utility function under two-factor Heston's stochastic volatility model. It is not possible to obtain an explicit solution because our financial market model is complicated. However, by using asymptotic analysis technique, we find the explicit forms of the approximations of the optimal value function and the optimal strategy for HARA utility function.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1329-1341
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• 2006

When X and Y have independent gamma distributions, we consider the testing problem for two gamma means. We propose a solution based on a Bayesian model selection procedure to this problem in which no subjective input is considered. The reference prior is derived. Using the derived reference prior, we compute the fractional Bayes factor and the intrinsic Bayes factors. The posterior probability of each model is used as a model selection tool. Simulation study and a real data example are provided.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.377-386
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• 2004

A technique that provides prediction intervals based on a model called an empirical linear model is discussed. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. HELP can be viewed as a technique that provides prediction (and confidence) intervals based on a factor analysis models do not typically have justifiable theory due to nonidentifiability, we show that the intervals are justifiable asymptotically.

• Journal of the Korea Society for Simulation
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• v.11 no.1
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• pp.59-70
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• 2002

This article presents the results of research to develop a descriptive model of firm-level productivity that will allow a myriad of factor interactions to be directly accounted for. The model is a linked set of equations that attempt to capture how changes in one-factor influences the level of another factor. and ultimately bottom-line performance. The model is coded in SIMAN. It is used to determine the best use of an infusion of funds should they go for additional automation, or training etc. An application of the model to U.S. industry is presented based on parameter values obtained through a national survey.

• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.489-493
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• 2018

Objective: This study was to identify whether working memory (WM) can be clearly subdivided according to auditory and visual modality. To do this, we administered the most recent and universal clinical WM measures in a mixed psychiatric sample. Methods: A total of 115 patients were diagnosed on the basis of DSM-IV diagnostic criteria and with MINI-Plus 5.0, a structured diagnostic interview. WM subtests of Korean version of Wechsler Adult Intelligence Scale-IV and Korean version of Wechsler Memory Scale-IV were administered to assess WM. Confirmatory factor analysis (CFA) was used to observe whether WM measures fit better to a one-factor or two-factor model. Results: CFA results demonstrated that a two factor model fits the data better than one-factor model as expected. Conclusion: Our study supports a modality model of WM, or the existence of modality-specific WM systems, and thus poses a clinical significance of assessing both auditory and visual WM tests.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.269-276
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• 2012

The objective of this short communication is to introduce several evaluation methods to crop model users because the evaluation of crop model performance is an important step to develop or select crop model. In this paper, mean error, mean absolute error, index of agreement, root mean square error, efficiency of model, accuracy factor and bias factor were explained and compared in terms of dimension and observed number. Efficiency of model and index of agreement are dimensionless and independent of number of observation. Relative root mean square, accuracy factor and bias factor are dimensionless and not independent of number of observation. Mean error and mean absolute error are affected by dimension and number of observation.