• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.73-77
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• 1986

Optimal input design problem for linear regression model with constrained output variance has been considered. It is shown that the optimal input signal for the linear regression model can also be realized as an ARMA process. Monte-Carlo simulation results show that the optimal stochastic input leads to comparatively better estimation accuracy than white input signal.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.475-484
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• 2004

This paper consider the testing problem of grouped heteroscedasticity in the linear regression model. We provide the Lagrange Multiplier(LM), Wald, Likelihood Ratio (LR) test statistis for testing of grouped heteroscedasticity. Monte Carlo experiments are conducted to study the performance of these tests.

• Journal of the Korean Mathematical Society
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• v.44 no.4
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• pp.835-844
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• 2007

This paper considers the problem of estimating the error distribution function in nonparametric regression models. Sufficient conditions are given under which the kernel estimator of the error distribution function based on nonparametric residuals satisfies the law of iterated logarithm.

• Journal of Korean society of Dental Hygiene
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• v.17 no.6
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• pp.1171-1182
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• 2017

Objectives: The purpose of the study was to investigate the correlation between critical thinking and problem-solving abilities in dental hygiene students. Methods: This is a cross-sectional study. A self-reported questionnaire was completed by 386 dental hygiene students enrolled in Gwangju Health university from August 30, 2017 to September 2, 2017. The general characteristics of the subjects, their critical thinking and problem-solving abilities were measured for the study. The tool to measure critical thinking was adapted from Yoon which had a Cronbach' alpha of 0.77. The tool for problem-solving ability was adapted from that used in Heppner & Petersen, which had a Cronbach' alpha of 0.77. The collected data are analyzed using ANOVA, Pearson's Correlation analysis, and multiple regression using SPSS/Win 18.0 program. Results: The results show that critical thinking scored 3.45 while problem solving ability scored 3.20. The correlation between critical thinking and problem-solving abilities was found to be strong. The strongest positive correlation in problem-solving ability was critical thinking (p<0.001). The multiple regression analysis suggests that the factors affecting problem solving ability of the subjects was statistically significant. The significant variables included critical thinking (${\beta}=0.440$) (p<0.001), satisfaction with one's major (${\beta}=0.108$) (p<0.05), interpersonal relationships (${\beta}=0.104$) (p<0.05) and academic performance (${\beta}=0.086$) (p<0.05) with an explanatory power of 38.3%. Conclusions: It is necessary to develop a curriculum and learning method for critical thinking and problem-solving abilities in the dental hygiene students.

• Journal of Engineering Education Research
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• v.23 no.6
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• pp.17-26
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• 2020

In this paper, the effect of daily creativity of engineering students on problem-solving ability is addressed through the dual mediating effect of teamwork competency and self-directed learning ability. To this end, a regression-based statistical mediation analysis has been performed on the dual mediation model in which daily creativity and problem solving ability were treated as independent and dependent variables respectively, and teamwork competence and self-directed learning ability were included as mediation variables. The analysis result confirmed that the daily creativity has direct effect on the problem-solving ability, as well as indirect effects through teamwork competence and self-directed learning ability. In particular, the serial mediating effect of teamwork competency and self-directed learning ability was also confirmed to be statistically significant in the relationship between daily creativity and problem-solving ability. This verifies that problem-solving ability can be improved not only directly by improving daily creativity but also indirectly by improving teamwork competence and self-directed learning ability. In addition, teamwork competency showed greater indirect effect on problem-solving ability than self-directed learning ability, so increasing teamwork competency has a more significant effect on improving problem-solving ability than increasing self-directed learning ability. Therefore, in order to develop better problem-solving ability, it is necessary to identify and improve the learners' teamwork competency first and to strive to create an environment where learners can solve problems based on mutual trust with their teammates.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.263-269
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• 2016

The purpose of this study is to challenge a computational regression-type problem, that is handling large-size data, in which conventional metamodeling techniques often fail in a practical sense. To solve such problems, regression-type boosting, one of ensemble model techniques, together with bootstrapping-based re-sampling is a reasonable choice. This study suggests weight updates by the amount of the residual itself and a new error decision criterion which constructs an ensemble model of models selectively chosen by rejection limits. Through these ideas, we propose AdaBoost.RMU.R as a metamodeling technique suitable for handling large-size data. To assess the performance of the proposed method in comparison to some existing methods, we used 6 mathematical problems. For each problem, we computed the average and the standard deviation of residuals between real response values and predicted response values. Results revealed that the average and the standard deviation of AdaBoost.RMU.R were improved than those of other algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.3
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• pp.61-66
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• 2003

In many multiple regression analyses, the “multi-collinearity” problem arises since some independent variables are highly correlated with each other. Practically, the Ridge regression method is often adopted to deal with the problems resulting from multi-collinearity. We propose a better alternative method using iteration to obtain an exact least squares estimator. We prove the solvability of the proposed algorithm mathematically and then compare our method with the traditional one.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.68-81
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• 1988

Testing procedures for a detection of change point in the regression model with correlated errors are discussed. A Bayesian approach is adopted and applied to a regression model with errors following an AR(1) model.

• Korean Journal of Mathematics
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• v.22 no.2
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• pp.289-305
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• 2014

In this paper we propose a new approach to the variable selection problem for a primary resolution and wavelet basis functions in wavelet regression. Most wavelet shrinkage methods focus on thresholding the wavelet coefficients, given a primary resolution which is usually determined by the sample size. However, both a primary resolution and the basis functions are affected by the shape of an unknown function rather than the sample size. Unlike existing methods, our method does not depend on the sample size and also takes into account the shape of the unknown function.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.623-630
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• 2003

Recently, Tanaka(1988) derived two influence functions related to an eigenvalue problem $(A-\lambda_sI)\upsilon_s=0$ of real symmetric matrix A and used them for sensitivity analysis in principal component analysis. In this paper, we deal with the perturbation expansions up to quadratic terms of the same functions and discuss the application to sensitivity analysis in principal component regression analysis(PCRA). Numerical example is given to show how the approximation improves with the quadratic term.