• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.765-776
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• 2006

In this paper we propose an estimation method on the regression model with randomly censored observations of the training data set. The weighted least squares support vector machine regression is applied for the regression function estimation by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed estimation method.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.25-34
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• 2004

In this paper we propose a prediction method on the regression model with randomly censored observations of the training data set. The least squares support vector machine regression is applied for the regression function prediction by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed prediction method.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.137-148
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• 2009

The purpose of this study is to implement variable selection algorithm which helps construct a reliable linear regression model. If we use all candidate variables to construct a linear regression model, the significance of the model will be decreased and it will cause 'Curse of Dimensionality'. And if the number of data is less than the number of variables (dimension), we cannot construct the regression model. Due to these problems, we consider the variable selection problem as a combinatorial optimization problem, and apply GA (Genetic Algorithm) to the problem. Typical measures of estimating statistical significance are $R^2$, F-value of regression model, t-value of regression coefficients, and standard error of estimates. We design GA to solve multi-objective functions, because statistical significance of model is not to be estimated by a single measure. We perform experiments using simulation data, designed to consider various kinds of situations. As a result, it shows better performance than LARS (Least Angle Regression) which is an algorithm to solve variable selection problems. We modify algorithm to solve portfolio selection problem which construct portfolio by selecting stocks. We conclude that the algorithm is able to solve real problems.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.2
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.159-164
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• 2000

In the study of the isotonic regression problem, several procedures for testing the homogeneity of a normal mean vector versus order restricted alternatives have been proposed since Barlow's trial(1972). In this paper, we consider the problem of testing the equality of two order restricted normal mean vectors based on the likelihood ratio principle.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.4
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• pp.438-448
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• 2013

Purpose: The purpose of this study was to investigate factors influencing clinical competence in nursing students. Method: The participants were 125 nursing students and data were collected from October 8 to December 18, 2010 using questionnaires with. Collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient and stepwise multiple regression. Results: There were significant correlations for creativity, problem-solving ability, self-directed learning ability, and clinical competence. The factor influencing clinical competence the most was creativity, followed by problem-solving ability, self-directed learning ability, and grade point average score. The regression model explained 37% of variance in clinical competence. Conclusion: The results indicate that for improvement in the clinical competence of nursing students, it is necessary to develop strategies and education programs to enhance creativity, problem-solving ability, and self-directed learning ability.

• Journal of Families and Better Life
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• v.31 no.1
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• pp.1-10
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• 2013

The purpose of this study was to examine the effects of teachers' responsiveness on teachers' strategies of problem behavior guidance. Teachers' responsiveness variables consisted of acceptance, sensitivity, consistency, warmth and teachers' strategies of problem behavior guidance variables consisted of positive proactive strategies, positive reactive strategies, negative reactive strategies. Subjects were 151 early childhood teachers in Seoul and Chungcheungnam-do. The collected data were analyzed using simple regression and hierarchical multiple regression. The main results of this study were as follows. Teachers' acceptance, sensitivity, consistency, warmth were positively related to teachers' positive proactive strategies and positive reactive strategies of problem behavior guidance. On the other hand, teachers' warmth was negatively related to teachers' negative reactive strategies. As results of examining relative effects of teachers' responsiveness on positive proactive strategies of problem behavior guidance, the influential variables were warmth and acceptance. The relative effects of teachers'responsiveness on positive reactive strategies of problem behavior guidance, the influential variables were sensitivity and acceptance. The relative effects of teachers' responsiveness on negative reactive strategies of problem behavior guidance, the only influential variable was warmth.

• Journal of Engineering Education Research
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• v.22 no.3
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• pp.32-40
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• 2019

This paper deals with the effects of teamwork competence on problem solving ability through the mediating effect of creative personality for the engineering students. For this purpose, a regression-based statistical mediation analysis has been performed for a simple mediation model in which teamwork competence and problem solving ability were treated as independent and dependent variables respectively, and creative personality was included as a mediation variable. The analysis results showed that the teamwork competence has direct effect on the problem solving ability as well as indirect effect through the creative personality. This result implies that the problem solving ability can be improved directly by improving the teamwork competence, and moreover, it can be further improved indirectly or through the mediation effect by improving the creative personality. Thus, in order to develop excellent problem solving ability, it is necessary to form team members in a balanced way between teamwork competence and creative personality in the team-based learning.

• Journal of muscle and joint health
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• v.29 no.2
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• pp.124-132
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• 2022

Purpose: The purpose of this study was to investigate the relationships among critical thinking disposition, problem solving ability, and triage competency in nurses working in Emergency Rooms (ERs). Methods: This cross-sectional study, conducted in August and September 2021, involved 118 ER nurses from three hospitals in the Gyeonggi-do metropolitan area. The data were analyzed using t-test, ANOVA, Scheffé test, Pearson correlation coefficients, and multiple linear regression analysis using SPSS for Windows version 25.0. Results: The mean score of triage competency among ER nurses was 87.63±15.65. In the regression model, age, ER experience, triage experience, critical thinking disposition, and problem solving ability predicted 52% of the triage competency. Both critical thinking disposition and problem-solving ability were noted to be significant (β=.32, p<.001; β=.36, p<.001, respectively). Conclusion: Critical thinking disposition and problem solving ability of ER nurses were identified as major factors in triage competency. To improve ER nurses' triage competency and enhance critical thinking disposition and problem solving ability, a systematic and ongoing program should be developed and implemented.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.215-227
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• 2007

Variable selection algorithm for Sliced Inverse Regression using penalty function is proposed. We noted SIR models can be expressed as generalized eigenvalue decompositions and incorporated penalty functions on them. We found from small simulation that the HARD penalty function seems to be the best in preserving original directions compared with other well-known penalty functions. Also it turned out to be effective in forcing coefficient estimates zero for irrelevant predictors in regression analysis. Results from illustrative examples of simulated and real data sets will be provided.