• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.197-206
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• 2000

For estimating missing cells in contingency table, we suggest an iterative method which extends IPF (Iterative Proportional Fitting) method. The suggested m~thod is not restricted by the number and the location of missing cells, and does not distort the given quasi-independency.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.29-40
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• 2019

Categorical data with non-responses are frequently observed in election poll surveys, and can be represented by incomplete contingency tables. To estimate supporting rates of candidates, the identification of the missing mechanism should be pre-determined because the estimates of non-responses can be changed depending on the assumed missing mechanism. However, it has been shown that it is not possible to identify the missing mechanism when using observed data. To overcome this problem, sensitivity analysis has been suggested. The previously proposed sensitivity analysis can be applicable only to two-way incomplete contingency tables with binary variables. The previous sensitivity analysis is inappropriate to use since more than two of the factors such as region, gender, and age are usually considered in election poll surveys. In this paper, sensitivity analysis suitable to an multi-dimensional incomplete contingency table is devised, and also applied to the 19th Korean presidential election poll survey data. As a result, the intervals of estimates from the sensitivity analysis include actual results as well as estimates from various missing mechanisms. In addition, the properties of the missing mechanism that produce estimates nearest to actual election results are investigated.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.145-157
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• 1994

For multivariate distributions satisfying stochastic ordering, we suggest maximum likelihood estimation with incomplete data via an EM algorithm. In this paper we restrict our attention to the contingency tables with partially cross-classified observations. We may use the existing isotonic regression program to implement EM algorithm, and we illustrate the estimation process through an example.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.5
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• pp.129-135
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• 2008

USWMM was developed as a drainage analysis system for estuarine urban areas by adding sluice gates on existing EPA SWMM5 through this study. For the purpose of reviewing, Ansungchon river was modeled with USWMM and calibration and verification were attempted at three observation stations. In comparison, another approach using HEC-HMS and HEC-RAS was applied to the area under the same condition. It turned out that USWMM resulting values were closer to the observed values than those of the HEC-HMS and HEC-RAS approach. USWMM's flow simulation through sluices were more realistic to sluice operation fields by adding incomplete submerged orifice flow equation and maintenance water level. In sum, USWMM can be seen as a general purpose tool for estuarine urban drainage analysis system.