• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.67-72
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• 2002

A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.113.2-113.2
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• 2005

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.237-250
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• 2002

Motivated by Cook's (1986) assessment of local influence by investigating the curvature of a surface associated with the overall discrepancy measure, this paper extends this idea to the linear regression model with AR(p) disturbances. Diagnostic for the linear regression models with AR(p) disturbances are discussed when simultaneous perturbations of the response vector are allowed. For the derived criterion, numerical studies demonstrate routine application of this work.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.467-477
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• 2006

A multidimensionality detecting procedure DETECT, based on conditional covariances between items, is extended and refined to deal with polytomous item data as well as binary one. A large body of simulation study shows extraordinary performance of DETECT in both enumerating degrees of multidimensionality in a test and discovering dimensionally distinctive item clusters. Real data study also provides very meaningful results, making DETECT a strong dimensionality assessment tool for the test data analysis.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.21-32
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• 1997

Robust regression based on M-estimator reduces and/or bounds the influence of outliers in the y-direction only. Therefore, when several influential observations exist, diagnostics in the robust regression is required in order to detect them. In this paper, we propose influence diagnostics in the robust regression based on M-estimator and its one-step version. Noting that M-estimator can be obtained through iterative weighted least squares regression by using internal weights, we apply the weighted least squares (WLS) regression diagnostics to robust regression.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.471-483
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• 1998

The influence of observations on the misclassification probability in multiple discriminant analysis under the equal covariance assumption is investigated by the local influence method. Under an appropriate perturbation we can get information about influential observations and outliers by studying the curvatures and the associated direction vectors of the perturbation-formed surface of the misclassification probability. We show that the influence function method gives essentially the same information as the direction vector of the maximum slope. An illustrative example is given for the effectiveness of the local influence method.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.231-245
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• 2000

This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.1-8
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• 1995

In generally speaking, the purpose of Environmental Impact Assessment(EIA) is to give the environment its due place in the decision-making process by clearly ealuating the environmental consequence of a proposed activity before action is taken. The introduction of conventional EIA is to be seen as an end product of a very long evolutionary process, starting with rudimentary but evolving pollution control measures for air, water, noise, land and chemicals, each governed by separate, and separately administered pieces of legislation. In EIA process, the measures of status, scoping, proposed mitigation and communication have not been very quantitative in their significancy. Of course, the determinations have uncertainity in the implications for significant impacts. To improve the determination of significant impacts, some more comprehensive methodologies of EIA has been proposed with the concepts of risk analysis in the proposed projects. The concepts of risk analysis has been introduced to the expression of human health impairment due to environmental pollutants since the early 1980's. The risk analysis being meant by the statistical significance of impact has a process quantitatively considering uncertainities and importances of ecological systems and human health as well. The process of risk analysis shows assessment, doseresponse in toxicity, exposure assessment and risk characterization. With the risk assessment, it could be suggested for the proper measurements against their anticipated risk in the EIA. This paper deals the priciples developing process and application of the risk-based analysis in EIA.

• Journal of Environmental Impact Assessment
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• v.16 no.2
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• pp.157-168
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• 2007

In case there is a need to run the multi-year urban scale air qulaity model, it is a difficult task due to the computational demand, requiring the statistical approach for the long time atmospheric environmental assessment. In an effort to approach toward long term urban assessment, the sixteen synoptic meteorological conditions are statistically classified from the estimated geostrophic wind speeds and directions of 850 hPa geopotential height field during 2000 ~ 2005. The geostrophic wind directions are subdivided into four even intervals (north, east, south, and west), geostrophic wind speeds into two classes(${\leq}5m/s$ and >5m/s), and daily mean cloud amount into 2 classes(${\leq}5/10$ and >5/10), which result into sixteen classes of the synoptic meteorological cases for each season. The frequency distributions for each 16 synoptic meteorological case are examined and some discussions on how these synoptic classifications can be used in the environmental assessment are presented.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.27-38
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• 2021

The physical condition assessment criteria of fill dam safety inspection are now weakly regulated and inappropriate for small agricultural reservoirs since these criteria have fundamental backgrounds suitable for large-scale dams. This study proposes the degree (critical values) of defects for the quantitative condition assessment of the embankment in order to prepare the condition assessment criteria for a small reservoir with a storage capacity of less than one (1) million cubic meters. The critical values of defects were calculated by applying the method that considers the size ratios based on the dimensional data of reservoirs, and the method of statistical analysis on the measured values of the defect degree which extracted from comprehensive annual reports on reservoir safety inspection. In comparison with the current criteria, the newly proposed critical values for each condition assessment item of the reservoir embankment are presented in paragraphs 4 and 6 of the conclusion. In addition, this study presents a method of displaying geometric figures to clarify the rating classification for condition assessment items with the two defect indicators.