• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.341-353
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• 2009

We consider sample-size determination problem motivated by comparative clinical trials where patient outcomes are characterized by a bivariate outcome of efficacy and safety. Thall and Cheng (1999) presented a sample size methodology for the case of bivariate binary outcomes. We propose a bivariate Wilcoxon-Mann-Whitney(WMW) statistics for sample-size determination for binary outcomes, and this nonparametric method can be equally used to determine sample sizes of ordinal outcomes. The two methods of sample size determination rely on the same testing strategy for the target parameters but differs in the test statistics, an asymptotic bivariate normal statistic of the transformed proportions in Thall and Cheng (1999) and nonparametric bivariate WMW statistic in the other method. Sample sizes are calculated for the two experimental oncology trials, described in Thall and Cheng (1999), and for the first trial example the sample sizes of a bivariate WMW statistic are smaller than those of Thall and Cheng (1999), while for the second trial example the reverse is true.

• Water for future
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• v.28 no.5
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• pp.117-127
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• 1995

The application and analysis for the scale considering GIUH model proposed by the authors in this issue have been performed for the leemokjung sub-basin in the Pyungchang basin one of IHP representative basin in Korea. Scales of topographic maps for model application and fractal analysis are 1:25,000, 1:50,000 and 1:100,000. The ratio between successive scales is therefore constant. Link lengths were measured using a curvimeter with the resolution of 1 mm. Richardson's method was employed to have fractal dimension of streams. Apparent alternations of parameters were found in accordance with variations of map scale. And this tendency could mislead physical meanings of parameters because model parameters had to preserve their own value in spite of map scale change. It was found that uses of fractal transform and Melton's law could help to control the scale problem effectively. This methodlogy also could emphasize the relationship between network and basin to the model. To verify the applicability of GIUH proposed in this research, the model was compared with the exponential GIUH model. It is proven that proposed 2-parameter gamma GIUH model can better simulate the corresponding runoff from any given flood events than exponential GIUH model. The result showed that 2-parameter gamma GIUH model and fractal theory could be used for deriving scale considered IUH of the basin.

• Journal of the Korea Computer Graphics Society
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• v.7 no.1
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• pp.37-49
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• 2001

We propose an optimization of mutual information for multiresolution image registration to represent useful information as integrated form obtaining from complementary information of multi modality images. The method applies mutual information as cost function to measure the statistical dependency or information redundancy between the image intensities of corresponding pixels in both images, which is assumed to be maximal if the images are geometrically aligned. As experimental results we validate visual inspection for accuracy, changning initial condition and addictive noise for robustness. Since our method uses the native image rather than prior feature extraction, few user interaction is required to perform the registration. In addition it leads to robust density estimation and convergence as applying non-parametric density estimation and stochastic multiresolution optimization.

• 한국벤처창업학회:학술대회논문집
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• 2024.04a
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• pp.17-20
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• 2024

우리는 대표적인 디지털 플랫폼인 온라인 음식 주문 배달 산업을 대상으로 디지털 경제의 긴꼬리 효과를 계량화한다. 특히, 코로나19 시기를 거치면서 음식배달플랫폼 입점으로 인한 긴꼬리 효과의 변화 양상을 고찰한다. 배달의민족에 입점한 음식점 15,000곳을 무작위로 선별하고 이들 매장의 2019년부터 2021년까지 전체 주문 정보를 취합(aggregation)하여 선형로그변환 후 기울기를 추정하여 디지털 경제의 긴꼬리 효과를 실증 분석하였다. 2019년부터 2021년까지 관찰기간 동안 음식 배달 플랫폼 활용 음식점 주비모수 분포의 긴꼬리 효과는 강건하게 관찰되었다. 이는 코로나19 이후 음식배달 플랫폼을 통한 음식점의 디지털 전환이 틈새시장 확장에 일정 부분 기여하였음을 의미한다. 또한, 긴꼬리 효과는 객단가가 높을수록 매출액 상위 집단일수록 더 커지는 반면, 비황금 시간대 매출비중이 높은 경우 긴꼬리 효과가 통계적으로 유의하게 증가하지 않았다. 이 결과는 피자, 족발 등 단가가 높고 비교적 배달서비스가 활발한 카테고리에서 음식 주문 및 배달 산업의 디지털 전환 효과가 증가한다는 업계 실무자들의 관찰과 부합한다. 타 업종에서도 상대적으로 경쟁이 치열한 시장 구분에서 디지털 경제의 긴꼬리 효과가 보다 강건하게 관찰될 것이라고 여겨진다. 음식점 간 경쟁강도가 상대적으로 약한 비황금시간대 매출비중이 긴꼬리 효과에 통계학적으로 유의한 영향을 주지 않는다는 실증결과 또한 동일한 함의가 있다.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.1
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• pp.23-32
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• 1999

A new numerical method using solution-adaptive grids (SAG) is developed to solve the Richards' equation (RE) for unsaturated flow in porous media. Using a grid generation technique, the SAG method automatically redistributes a fixed number of grid points during the flow process, so that more grid points are clustered in regions of large solution gradients. The method uses the coordinate transformation technique to employ a new transformed RE, which is solved with the standard finite difference method. The movement of grid points is incorporated into the transformed RE, and therefore all computation is performed on fixed grid points of the transformed domain without using any interpolation techniques. Thus, numerical difficulties arising from the movement of the wetting front during the infiltration process have been substantially overcome by the new method. Numerical experiments for an one-dimensional infiltration problem are presented to compare the SAG method to the modified Picard method using a fixed grid. Results show that accuracy of a SAG solution using 41 nodes is comparable with the solution of the fixed grid method using 201 nodes, while it requires only 50% of the CPU time. The global mass balance and the convergence of SAG solutions are strongly affected by the time step size (Δt) and the weighting parameter (${\gamma}$) used for generating solution-adaptive grids. Thus, the method requires automated readjustment of Δt and ${\gamma}$ to yield mass-conservative and convergent solutions, although it may increase computational costs. The method can be effective especially for simulating unsaturated flow and other transport problems involving the propagation of a sharp-front.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2805-2812
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• 2018

The methylation score, expressed as a percentage of the methylation status data derived from the iterative sequencing process, has a value between 0 and 1. It is contrary to the assumption of normal distribution that simply applying the t-test to examine the difference in population-specific methylation scores in these data. In addition, since the result may vary depending on the number of repetitions of sequencing in the process of methylation score generation, a method that can analyze such errors is also necessary. In this paper, we introduce the symbolic data analysis and the interval K-S test method which convert observation data into interval data including uncertainty rather than one numerical data. In addition, it is possible to analyze the characteristics of methylation score by using Beta distribution without using normal distribution in the process of converting into interval data. For the data analysis, the nature of the proposed method was examined using sequencing data of actual patients and normal persons. While the t-test is only possible for the location test, it is found that the interval type K-S statistic can be used to test not only the location parameter but also the heterogeneity of the distribution function.

• Journal of the Korean earth science society
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• v.29 no.3
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• pp.263-279
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• 2008

This study is concerned with the optimization of models using MM5 and WRF mesoscale numerical models to simulate strong sea surface winds, such as that of typhoon Shanshan on 17 September 2006, and the Siberian high event on 16 December 2006, which were selected for displaying the two highest mean wind speeds. The model optimizations for the lowest level altitude, physical parameters and horizontal resolution were all examined. The sea surface wind values obtained using a logarithmic function which takes into account low-level stability and surface roughness were more accurate than those obtained by adjusting the lowest-level of the model to 10 m linearly. To find the optimal parameters for simulating strong sea surface winds various physical parameters were combined and applied to the model. Model grid resolutions of 3-km produced better results than those of 9-km in terms of displaying accurately regions of strong wind, low pressure intensities and low pressure mesoscale structures.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.617-626
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• 2009

A series of recent papers reported that the inter-gene correlations in Affymetrix microarray data sets were strong and long-ranged, and the assumption of independence or weak dependence among gene expression signals which was often employed without justification was in conflict with actual data. Qui et al. (2005) indicated that applying the nonparametric empirical Bayes method in which test statistics were pooled across genes for performing the statistical inference resulted in the large variance of the number of differentially expressed genes. Qui et al. (2005) attributed this effect to strong and long-ranged inter-gene correlations. Klebanov and Yakovlev (2007) demonstrated that the inter-gene correlations provided a rich source of information rather than being a nuisance in the statistical analysis and they developed, by transforming the original gene expression sequence, a sequence of independent random variables which they referred to as a ${\delta}$-sequence. We note in this report using two cDNA microarray data sets experimented in this country that the strong and long-ranged inter-gene correlations were still valid in cDNA microarray data and also the ${\delta}$-sequence of independence could be derived from the cDNA microarray data. This note suggests that the inter-gene correlations be considered in the future analysis of the cDNA microarray data sets.

• The Korean Journal of Malacology
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• v.29 no.4
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• pp.325-334
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• 2013

The purpose of this paper is to compare and analyze family variations for growth-related traits of Pacific abalone, Haliotis discus hannai. Genetic parameters and breeding values were estimated using all measurement data like shell length, shell width, and total weight as 18-month-old growth traits of 5,334 individuals of selected third generation's Pacific abalone produced in 2011. Family variations of 865 individuals of the upper 10 families with the largest number were inspected. Overall mean in phenotypic traits of 18-month-old Pacific abalone which was investigated in this study showed 54.5 mm of shell length, 36.8 mm of shell width and 21.3 g of total weight respectively. And, variation coefficient of total weight was 51.0%, so variability of data was shown to be higher than 21.1% of shell length and 20.7% of shell width. The family effects showed significant difference by each family (p < 0.05), and heritability of shell length, shell width, and total weight was medium with 0.370, 0.382, and 0.367 respectively. So it is considered that family selection is more advantageous than individual selection. On the basis of breeding values of estimated shell length and total weight, to investigate distribution and ranking by each individual about the upper 10 families with the largest number of individuals, the values were used by being changed into standardized breeding values. Based on shell length, it was investigated that the individual number of the upper 5.4% is 152 and the number of the lower 5.4% is 8. In case of total weight, it was inspected that the individual number of the upper 5.4% is 164 and the number of the lower 5.4% is 1. Like these, phenotypic and genetic diverse variations between families could be checked. By estimating genetic parameters and breeding values of a population for production of the next generation, if they are used properly in selection and mating, it is considered that more breeding effects can be expected.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.37-47
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• 2013

A Q-Q plot is an effective and convenient graphical method to assess a distributional assumption of data. The primary step in the construction of a Q-Q plot is to obtain a closed-form expression to represent the relation between observed quantiles and theoretical quantiles to be plotted in order that the points fall near the line y = a + bx. In this paper, we introduce a Q-Q plot to assess goodness-of-fit for inverse Gaussian distribution. The procedure is based on the distributional result that a transformed random variable $Y={\mid}\sqrt{\lambda}(X-{\mu})/{\mu}\sqrt{X}{\mid}$ follows a half-normal distribution with mean 0 and variance 1 when a random variable X has an inverse Gaussian distribution with location parameter ${\mu}$ and scale parameter ${\lambda}$. Simulations are performed to provide a guideline to interpret the pattern of points on the proposed inverse Gaussian Q-Q plot. An illustrative example is provided to show the usefulness of the inverse Gaussian Q-Q plot.