• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.77-91
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• 2002

This paper considers a functional regression model with truncated errors in explanatory variables. We show that the ordinary least squares (OLS) estimators produce bias in regression parameter estimates under misspecified models with ignored errors in the explanatory variable measurements, and then propose methods for analyzing the functional model. Fully parametric frequentist approaches for analyzing the model are intractable and thus Bayesian methods are pursued using a Markov chain Monte Carlo (MCMC) sampling based approach. Necessary theories involved in modeling and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed methods.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.885-893
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• 2013

This paper considers Bayes estimations of the small area means under Fay-Herriot model with measurement errors. We provide empirical Bayes predictors of small area means with the corresponding jackknifed mean squared prediction errors. Also we obtain hierarchical Bayes predictors and the corresponding posterior standard deviations using Gibbs sampling. Numerical studies are provided to illustrate our methods and compare their eciencies.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.793-802
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• 1997

A sampling plan is presented for situations where sampling inspection is based on the quality characteristic of interest and items in rejected lots are screened based on a correlated variable. A cost model is constructed which involves the costs of misclassification errors, sampling and screening inspections. A method of finding optimal values of sample size, acceptance number and cutoff value on the correlated variable is presented, and numerical studies are given.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.100-117
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• 1985

This paper describes an outline of the sampling design for crop area survey and product survey in Korea. The design attempts to from a double statification, to obtain an efficient allocation of the sample and to reduce the sampling error by establishign crop concentrated strata. The optimum numbers of sample field and sample plot are investigated. The design is made it possible to reduce the sampling errors as well as to reduce the sample size further than the present survey.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.411-421
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• 2016

Large frequency limiting distributions of two errors in realized covariance are investigated under noisy and non-synchronous high frequency sampling situations. The first distribution characterizes increased variance of the realized covariance due to noise for large frequency and the second distribution characterizes decreased variance of the realized covariance due to discretization for large frequency. The distribution of the combined error enables us to determine the sampling frequency which depends on a nuisance parameter. A consistent estimator of the nuisance parameter is proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.11 no.18
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• pp.27-34
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• 1988

This study is concerned with the development of the economic sampling inspection plan when it is possible to carry out a nondestructive screening inspection for the rejected lots by substitutive characteristics closely related to the original quality characteristic. It is assumed that the probabilities of those errors depend linearly on the fraction defective of the process sampling inspection policy for isolated lot is studied where the probability of accepting the lot with bad quality from the results of sampling inspection is restricted to be small.

• Journal of Korean Academy of Nursing Administration
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• v.19 no.1
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• pp.28-38
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• 2013

Purpose: Human factor is one of the major causes of medication errors. The purpose of this study was to identify nurses' perception and experience of medication errors, examine the relationship of Dominance, Influence, Steadiness, Conscientiousness (DISC) behavior patterns and medication errors by nurses. Methods: A descriptive survey design with a convenience sampling was used. Data collection was done using self-report questionnaires answered by 308 nurses from one university hospital and two general hospitals. Results: The most frequent DISC behavioral style of nurses was influence style (41.9%), followed by steadiness style (23.7%), conscientiousness style (20.4%), and dominance style (14.0%). Differences in the perception and experience level of medication errors by nurses' behavioral pattern were not statistically significant. However, nurses with conscientiousness style had the lowest scores for in experience of medication errors and the highest scores for perception of medication errors. Conclusion: The results of this study show that identification of the behavior pattern of nurses and application of this education program can prevent medication errors by nurses in hospitals.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.1-9
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• 2014

This paper discusses the problem of estimation of finite population mean in double sampling for stratification. In fact, ratio and product type exponential estimators of population mean are proposed in double sampling for stratification. The biases and mean squared errors of proposed estimators are obtained upto the first degree of approximation. The proposed estimators have been compared with usual unbiased estimator, ratio and product estimators in double sampling for stratification. To judge the performance of the proposed estimators an empirical study has been carried out.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.941-948
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• 2006

In this study, the new method for reliability estimation is proposed using kriging metamodel. Kriging metamodel can be determined by appropriate sampling range and sampling numbers because there are no random errors in the Design and Analysis of Computer Experiments(DACE) model. The first kriging metamodel is made based on widely ranged sampling points. The Advanced First Order Reliability Method(AFORM) is applied to the first kriging metamodel to estimate the reliability approximately. Then, the second kriging metamodel is constructed using additional sampling points with updated sampling range. The Monte-Carlo Simulation(MCS) is applied to the second kriging metamodel to evaluate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.658-663
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• 1987

The new controller developed here, which is the facility with only one measurement, is a new concept for the level controller of the existing nuclear steam generator. A MACS (Microcomputer-based Adaptive Control System of a Steam Generator) is quite practical and efficient, and has also simple structure and higher flexibility in the installment for actual plant. A key ingredient of this system is adaptive regulator which can calculate adaptive, optimal valve position in response to changes in the dynamics of the process and the disturbances. In spite of many difficulties in the steam generator water level control at low power, it can be concluded from the experimental and simulation results, that the MACS can provide optimal, robust steam generator level control from zero to full power. The amount of the control input effort can be reduced by adjusting the weighting factor. However, the steady state water level errors are generated. To avoid the steady errors, the different adaptive algorithm should be investigated in the future. The 3 second sampling time is acceptable for this system. However, action should be taken to shorten the sampling time for better digital control.