• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.635-644
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• 2008

We consider estimation of reliability P(Y

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.783-792
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• 2007

We consider estimation of reliability P(Y

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.325-332
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• 2008

We consider estimation of reliability P(Y < X) and distribution of the ratio when X and Y are independent uniform random variable and power function random variable, respectively and also consider the estimation problem when X and Y are independent uniform random variable and a half-normal random variable, respectively.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.195-198
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• 2006

In this paper, we propose a 2dimension Control Chart. Suggested which Control chart augments Schwart Control chart which is 1-dimensional and Independent variable and dependent variable interrelationship by using control chart. Schwart control chart cannot use input variable and output variable together. In this paper, we try to analysis input variable and output variable dependent and effect. So called 2-dimensional control char.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.967-977
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• 2008

We consider densities of quotient Y/X and ratio X/(X+Y), and estimation of reliability P(Y

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.77-84
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• 1998

ARES plot (Cook and Weisberg, 1987) idea is applied to a multiple regression model in which the relation between a response variable and some independent variable is nonlinear. This method is expected to show the impact on the function to which and independent variable should be transformed, as a variable is smoothly added to the model.

• Journal of the Korea Safety Management & Science
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• v.26 no.2
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• pp.107-115
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• 2024

This study conducted frequency analysis, reliability analysis, descriptive statistics, and correlation analysis to determine the impact of quality control managers' perception and implementation of KS certification factory inspection evaluation items on follow-up management. Through a multiple linear regression model, the influence of KS certification officer's awareness and implementation of KS certification factory inspection on post management was found to have a positive (+) influence on post management, with implementation having a greater influence on post management than awareness. It was having an impact. The independent variable (perception) has a statistically significant impact on the mediating variable (execution), and in the stage of verifying the mediating effect, the influence of the independent variable (perception) on the dependent variable (follow-up management) has a statistically significant impact. , In the stage where the independent variable (perception) and the mediator (implementation) are input simultaneously, both the independent variable and the mediator have a statistically significant effect on the dependent variable, indicating that there is a mediation effect.

• The Journal of Fisheries Business Administration
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• v.40 no.3
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• pp.169-187
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• 2009

This study analyzes the long and short term effect of exchange rate on the import of Korea's fisheries focussed on main fisheries imported from China. The estimation models consist of the following contents. The first model consists of one dependent variable-import quantity of fisheries imported from China(${IMQ_t}^{CHO}$) and three independent variables-${RP_t}^{CHO}$, $EXC_t$ and $GDP_t$. The second one-one dependent variable-import quantity of fisheries imported from China(${JMQ_t}^{NAG})$ and three independent variables-${RP_t}^{NAG}$, $EX_t$ and $GDP_t$. the third one-one dependent variable-import quantity of fisheries imported from China(${IMQ_t}^{AH}$) and three independent variables-${RP_t}^{AH}$, $EX_t$ and $GDP_t$. the forth one-one dependent variable-import quantity of fisheries imported from China(${IMQ_t}^{KO}$) and three independent variables-${RP_t}^{KO)$, $EX_t$ and $GDP_t$. the last one is made up of one dependent variable-import quantity of fisheries imported from China(${IMQ_t}^{GAL}$) and three independent variables-, ${RP_t}^{GAL}$, $EX_t$ and $GDP_t$. and. The estimation results show that exchange rate of the independent variables are statistically significant in only the first model. The figure is elastic. Especially, the effect of exchange rate in first model is grater than that of the. However, the effect of exchange rate, one of independent variables in the ECM, is not statistically significant.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.227-235
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• 1993

Calibration relates the estimation of independent variable which rquires more effort or expense than dependent variable does. It would be provided with high accuracy because a little change of the result of independent variable cn cause a serious effect to the human being. Usual statistical analysis assumes the normality of error distribution or linearity of data. It is desirable to analyze the data without those assumptions for the accuracy of the calibration. In this paper, we calibrated the data nonparametrically without those assumptions and derived confidence interval estimate for the independent variable. As a method, we used kernel method which is popular in modern statistical branch. We derived bootstrap confidence interval estimate from the bootstrap confidence band.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.163-170
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• 1996

An errors-in-variables model (EVM) differs from the classical regression model in that in the former the independent variable is also subject to error. This paper shows that to assess the applicability of the ordinary least squares (OLS) estimation procedure to the EVM, the relative dispersion of the independent variable to its error variance must be also considered in addition to Mandel's criterion. The effect of physically reducing the variance of errors in the independent variable on the performance of the OLS slope estimator is also discussed.