• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.561-571
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• 2015

When we consider an optimal design to predict the response corresponding to the point outside the design region, we are extremely careful about choosing the design criteria for selecting the support points. The assumed model and its accompanying error structure should be assumed to extend beyond the design region for the selected design criteria to be valid. Thus, we modify the existing design criteria such as extrapolation-optimality to be suited to those situations. We propose some maximin approaches in this paper. Simple and quadratic regression models are tested to find the basic characteristics of such maximin approaches. Some main findings are discussed in the conclusion.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.177-187
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• 1997

This article considers the power performance of the tests in unbalanced two way mixed linear models with one fixed factor. The generalized least squares (GLS) F statistic testing no differences among the effects of the levels of the fixed factor is estimated using Henderson's method III, minimum norm quadratic unbiased estimator (MINQUE) with prior guess 1, maximum likelihood (ML) and resticted maximum likelihood (REML). We investigate the power performance of these test statistics. It can be shown, through simulation, that the GLS F statistics using four estimators produce similar type I error rates and power performance.

• KDI Journal of Economic Policy
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• v.28 no.2
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• pp.1-49
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• 2006

Considering the fact that households' demographic characteristics affect consumption decision, it is conjectured that rapid demographic changes would lead to a substantial change in the composition of private consumption expenditure. This paper estimates the demand functions of various consumption items by applying the Quadratic Almost Ideal Demand System(QUAIDS) model to Household Income and Expenditure Survey data, and then provides a long-term forecast of the composition of household consumption expenditure for 2005-2020. The paper shows that Korea's consumption expenditure will maintain the recent years' rapid change, of which a considerable portion is due to rapid demographic changes. Results of the paper can be utilized in forecasting the change in the industrial structure of the economy, as well as in firms' investment planning.

• Journal of Science Education
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• v.33 no.1
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• pp.100-110
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• 2009

This study analyzes the factors influencing interest on scientific subject and its change in Korean youth by using a sample from KEEP(Korea Education and Employment Panel 1-4) data. The results are as follows: First, the interest on scientific subject of Korean youth show quadratic curve. Also, the interrelationship between intercept and slope of subject interest is -.205 but it is not statistically significant Second, analysis of Latent Growth Models shows that self-esteem, academic achievement, school culture/climates and high school tracks are found to be a statistically significant factor on the intercept of subject interest These findings indicate that the interest on scientific subject of the Korean youth show a quadratic curve and various factors such as self-esteem, academic achievement and school culture/climates are much more influential on it.

• Journal of Navigation and Port Research
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• v.30 no.10 s.116
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• pp.869-875
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• 2006

This paper presents the method for developing an optimum hull form with minimum wave resistance using SQP(sequential quadratic programming) as an optimization technique. The wave resistance is evaluated by a Rankine source panel method with non-linear free surface conditions and the ITTC 1957 friction line is used to predict the frictional resistance coefficient. The geometry of the hull surface is represented and modified using NURBS(Non-Uniform Rational B-Spline) surface patches. To verity the validity of the developed program the numerical calculations for Wigley hull and Series 60( $C_B=0.6$) hull have been performed and the results obtained by the numerical calculations have been compared with the original hulls.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.47-53
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• 2005

This paper presents the method for developing an optimum hull form with minimum wave resistance using SQP(sequential quadratic programming) as an optimization technique. The wave resistance is evaluated by a Rankine source panel method with non-linear free surface conditions and the ITTC 1957 friction line is used to predict the frictional resistance coefficient. The geometry of the hull surface is represented and modified using NURBS(Non-Uniform Rational B-Spline) surface patches. To verity the validity of the developed program the numerical calculations for Wigley hull and Series 60(C${_B}$=0.6) hull had been performed and the results obtained after the numerical calculations had been compared with the original hulls.

• Food Science and Preservation
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• v.14 no.5
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• pp.469-473
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• 2007

The optimal formula for non-frozen pound cake was sought using a central composite design with a quadratic model, by response surface methodology (RSM). Behavior on supercooling, freezing time, theological properties, and sensory attributes of pound cake were studied by using various concentrations of sugar, sorbitol, and glycerol. The freezing temperature of standard pound cake was $-16.16^{\circ}C$. The hardness, freezing point temperature, and sensory properties were shown as a quadratic relationship whereas moisture content was analyzed by a linear model. Optimized formula for non-frozen cake were suggested to include (sugar:sorbitol:glycerol) 77.6:0.0:20.4, 60.0:32.8:16.4, and 70.8:11.2:19.6 (all % of total sugar) by RSM. The freezing tines of optimized non-frozen pound cake were reduced by $27{\sim}45%$. The freezing Points of optimized pound cake were depressed below $-20^{\circ}C$. Sorbitol and glycerol may be used as cryoprotectants and preserve the desired sensory attributes of pound cake at low temperatures.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.103-115
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• 2007

In this paper we studied the small sample asymptotic inference for the autoregressive coefficient in AR(1) model. Based on saddlepoint approximations to the distribution of quadratic forms, we suggest a new approximation to the distribution of the estimators of the noncircular autoregressive coefficients. Simulation results show that the suggested methods are very accurate even in the small sample sizes and extreme tail area.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.293-308
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• 1997

Sliced inverse regression is a method for reducing the dimension of the explanatory variable X without going through any parametric or nonparametric model fitting process. This method explores the simplicity of the inverse view of regression; that is, instead of regressing the univariate output varable y against the multivariate X, we regress X against y. In this article, we propose bivariate sliced inverse regression, whose method regress the multivariate X against the bivariate output variables $y_1, Y_2$. Bivariate sliced inverse regression estimates the e.d.r. directions of satisfying two generalized regression model simultaneously. For the application of bivariate sliced inverse regression, we decompose the output variable y into two variables, one variable y gained by projecting the output variable y onto the column space of X and the other variable r through projecting the output variable y onto the space orthogonal to the column space of X, respectively and then estimate the e.d.r. directions of the generalized regression model by utilize two variables simultaneously. As a result, bivariate sliced inverse regression of considering the variable y and r simultaneously estimates the e.d.r. directions efficiently and steadily when the regression model is linear, quadratic and nonlinear, respectively.

• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.179-197
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• 2016

The development of overseas resource is a driving force to secure the energy security in Korea with low sufficiency rate of energy. This paper analyzes the effect of overseas oil resource development on the economy by presenting a real business cycle model with consolidated energy price index. A linear-quadratic dynamic programming is adopted to raise computational transparency and efficiency. The analysis shows that the overseas oil resource development project during 2010 and 2012 decreases the energy price by 1.2% per annum which effect is equivalent to the positive 0.47% to the GDP. The implication calls for steady and robust support for overseas resource development projects to enhance energy resilience.