• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.1-7
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• 2018

The purpose of this study is to compare and analyze the response time of three mobile portal sites in Korea using distributions. The research subjects are the mobile portal site of Naver, Daum, and Nate. The experiment period is six years from April 18, 2012 when mobile portals started to activate, to April 17, 2018. The number of experiments is 4,060. Histograms and percentages were used for the distribution comparisons. For the theoretical comparison, Chi-Square test is adopted as a parametric method, and Kolmogorov-Smirnov test is as a nonparametric method. Naver was the fastest of all four methods, the next was Nate, the next was the slowest. The same result was obtained in terms of average response speed. These results are in contradiction to the results of the wired portal. Naver is a strategy to increase the response speed in accordance with the characteristics of media. Daum is a strategy to increase the contents at the cost of response speed. As for classification, we divide the response time into "Comfortable", "Tolerable", "Feedback", "Leave" according to response time. The ratio of more than 7 seconds that users leave called as "Leave" is 1.18% for Naver, 11.70% for Daum, and 1.5% for Nate. As Daum is overwhelmingly high, the response time is very much in need of improvement. In addition, we show the response time of three mobile portals needs to be reduced We hope that the results of this paper will facilitate technology competition to increase the response speed of mobile portals.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.281-290
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• 2013

It is well known that the DD-plot is a useful graphical tool for non-parametric classification. In this paper, we propose another use of DD-plot for detecting the out-of-control state in multivariate process. We suggested a dynamic version of DD-plot and its accompanying a quality index plot in such case.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.383-392
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• 2022

Culture technology is contributing to the creation of new values through convergence with other industries. The government is also actively investing in R&D in this field to secure competitiveness. In this study, the R&D efficiency of culture technology is analyzed by characteristics. Data envelopment analysis and non-parametric tests are performed on 968 national research projects in 2016-2019. As a result, it is confirmed that there are a difference in R&D efficiency according to the characteristics of national research projects in culture technology sector. This suggests that when planning national research projects for culture technology, these characteristics should be taken into consideration and strategically promoted.

• Asia Marketing Journal
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• v.9 no.2
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• pp.23-47
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• 2007

A new chi-square test is proposed to assess significance of attributes for nonparametric conjoint models. The key idea is to form subsets of rankings and test the dependence between the attribute levels and the sets of rankings. The null hypothesis states that the rankings for profiles with the focal attribute are distributed randomly among the sets of rankings. The approach is simple, easy to use, and can be applied at the individual level as well as at the aggregate level. It can be used for the trade-off approach as well as for the full profile approach.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.69-87
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• 2014

This paper suggests a conditional simulation framework based on multiple data transformations for geostatistical simulation of compositional data. First, log-ratio transformation is applied to original compositional data in order to apply conventional statistical methodologies. As for the next transformations that follow, minimum/maximum autocorrelation factors (MAF) and indicator transformations are sequentially applied. MAF transformation is applied to generate independent new variables and as a result, an independent simulation of individual variables can be applied. Indicator transformation is also applied to non-parametric conditional cumulative distribution function modeling of variables that do not follow multi-Gaussian random function models. Finally, inverse transformations are applied in the reverse order of those transformations that are applied. A case study with surface sediment compositions in tidal flats is carried out to illustrate the applicability of the presented simulation framework. All simulation results satisfied the constraints of compositional data and reproduced well the statistical characteristics of the sample data. Through surface sediment classification based on multiple simulation results of compositions, the probabilistic evaluation of classification results was possible, an evaluation unavailable in a conventional kriging approach. Therefore, it is expected that the presented simulation framework can be effectively applied to geostatistical simulation of various compositional data.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.587-598
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• 2006

The number of variables exceeds the number of samples in microarray data. We propose a nonparametric local linear logistic classification procedure using orthogonal components for classifying high-dimensional microarray data. The proposed method is based on the local likelihood and can be applied to multi-class classification. We applied the local linear logistic classification method using PCA, PLS, and factor analysis components as new features to Leukemia data and colon data, and compare the performance of the proposed method with the conventional statistical classification procedures. The proposed method outperforms the conventional ones for each component, and PLS has shown best performance when it is embedded in the proposed method among the three orthogonal components.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.5
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• pp.845-853
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• 1997

본 논문의 목적은 Rogers의 혁신도입이론(1983)을 이론적 배경으로 하여, QR효과와 QR도입의 관계를 규명하고, QR 도입/미도입의 이유를 조사하였다. 조사대상은 미국 전역에서 무작위로 추출된 306개의 의류업체를 대상으로 설문조사를 실시하였다. 설문응답률은 47% (n=103)였고, 자 료의 분석은 기술통계와 비모수통계기 법을 사용하였다. QR 효과를 높게 지각하는 대상기업이 QR 도입기업으로 분류되었다. 설문응답 기업의 940A가 QR도입은 변화하는 시장수요에 대한 대응력과 재공품의 감소효과를 제공한다고 응답했다. QR도입효과를 지각하면서도 QR을 도입하지 못한 가장 큰 이유는 QR의 초기투자비용 때문인 것으로 나타났다. 정부차원의 의류중소기업 지원대책 마련 방안과 정확한 QR교육이 시급하다.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.517-541
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• 2019

According to the OECD (2015) and UN (2017), Korea was classified as an immigration country. The designation as an immigration country means that net migration will remain positive and international migration is likely to affect population growth. KOSTAT (2011) used a model with more than 15 parameters to divide sexes, immigration and emigration based on the Wilson (2010) model, which takes into account population migration factors. Five years later, we assume the average of domestic net migration rate for the last five years and foreign government policy likely quota. However, both of these results were conservative estimates of international migration and provide different results than those used by the OECD and UN to classify an immigration country. In this paper, we proposed a stochastic projection on international migration using nonparametric model (FDM by Hyndman and Ullah (2007) and Coherent FDM by Hyndman et al. (2013)) that uses a functional data model for the international migration data of Korea from 2000-2017, noting the international migration such as immigration, emigration and net migration is non-linear and not linear. According to the result, immigration rate will be 1.098(male), 1.026(female) in 2018 and 1.228(male), 1.152(female) in 2025 per 1000 population, and the emigration rate will be 0.907(male), 0.879(female) in 2018 and 0.987(male), 0.959(female) in 2025 per 1000 population. Thus the net migration is expected to increase to 0.191(male), 0.148(female) in 2018 and 0.241(male), 0.192(female) in 2025 per 1000 population.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1271-1280
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• 2010

We have used multifactor dimensionality reduction (MDR) method to study genegene interaction effect of statistical model in general. But, MDR method could not be applied in the continuous data. In this paper, continuous-type data by the support vector machine (SVM) algorithm are proposed to the MDR method which provides an introduction to the technique. Also we apply the method on the identify major interaction effects of single nucleotide polymorphisms (SNPs) responsible for economic traits in a Korean cattle population.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.86-98
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• 2014

This study examined a long-standing issue with its perverse results in the Korean capital markets, such as any variant financial profiles over time, affecting capital structure for the firms belonging to the chaebols. It may be of interest to identify these components from the perspectives of international investors and domestic policy makers to implement their contingent strategies on the target leverage, since the U.S. financial turmoils in the late 2000s. Regarding the evidence from the three hypothesis tests on the firms in the chaebols, this research found that the control variabels measuring profitability, business risk, and non-debt tax shields, showed their statistically significant relationships with the different types of a debt ratio. While FCFF(free cash flow to the firm) showed its significant influence to discriminate between the firms in the chaebols and their counterparts, not belonging to the chaebols, BDRELY as the ratio of liabilities to total assets, comprising the enhanced 'Dupont' system, only showed its statistically significant effect on leverage in the context of the parametric and nonparametric tests. In line with the results obtained from the present research, one may expect that a firm in the Korean chaebol, may control or restructure its present level of capital structure to revert to its target optimal capital structure towards maximizing the shareholders' wealth.