• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1005-1021
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• 2007

Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.953-959
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• 2002

계절유행상품의 수요는 연중 성수기가 길지 않고 매년 유행과 제품디자인 변화가심한 경향이 있어 수요예측에 과거의 판매정보의 유용성이 크지 않다. 성수기 초반의 수요가 연간 수요결정에 매우 중요하며 후반부수요가 급격히 감소하는 특성이 있다. 반면 이월상품의 잔존가치가 매우 낮지만 매출마진이 높아 수요예측의 정확도에 따라 수익률이 큰 영향을 받는다. 이러한 이유로 기존의 수요예측방법을 계절상품에 적용하기에 무리가 따르며 예측오차의 비용이 매우 커서 계절상품 관리에 이용할 수 없다. 본 연구에서 성수기를 하위기간으로 구분하여 시즌 초반부 수요발생시점을 측정하여 초반부 기간별수요량을 구하고 이를 근거로 기간 누적수요비율을 quantile regression에 의거 추정하여 기간별 수요량과 전제 수요량을 예측하는 방법을 제시하고 모의자료를 사용하여 이 모형의 우수성을 평가하였다.

• Analyses & Alternatives
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• v.3 no.1
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• pp.135-157
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• 2019

The linkages between asset prices and macroeconomic outcomes are long-standing issue to both economists and monetary authorities. This paper explores the impact of asset prices on output and price in China. It focuses on the impacts of asset prices on the low quantiles of GDP gap and high quantiles of price gaprespectively. The main findings are the following: the influence of stock price gap, stock returns, and money growth on the different quantile of GDP gap and price gap are noticeable different, and there are significant impacts on the left tail of GDP gap distribution and on the right tail of price gap distribution. This implies that the results coming from simple regression will underestimate the economic risk imposed by asset price volatility. Moreover, these results also provide the caveat that one should cautiously distinguish the meaning of asset price gap and asset price growth rate and use them, through their contents are similar in some sense. One implication for monetarypolicy is that authority should interpret the relationship between asset prices and macro-economy in wider perspectives, and make the policy decision taking the impacts of asset prices on the tails of economy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7134-7147
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• 2014

This study examined one of the contemporary issues that may be interesting to academics and practitioners regarding the driving force of the growth rate for the firms belonging to the chaebols in the Korean capital markets. With respect to the empirical results obtained from two hypothesis tests, the first hypothesis was to identify any financial determinants on the growth rate by applying both dynamic panel data and static panel data models. The debt ratios relevant to the book- and market-value showed their positive relationships with the DV of GROWTH1, along with other significant IDVs such as one-period lagged DV of GROWTH_1, SIZE1 and FOS with statistical significance. Second, by employing conditional quantile regression (CQR) analysis, the control variables, such as ROA, SMARKET, time dummy variable of F2010 and F2011, and the industry dummies of IND3 and IND10, provided evidence of their significant influences on DV of GROWTH1.

• Journal of Technology Innovation
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• v.21 no.1
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• pp.27-57
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• 2013

The projects of agricultural R&D investments have been evaluated largely on the basis of efficiency better than equity although both criteria are equally critical in that major fund source of agricultural R&D investments is public budget. In this study, I focus on equity aspects by identifying the heterogeneous impacts of public knowledge created by R&D on farm efficiencies by farm income levels using bias-corrected DEA and quantile regression with panel data. The findings indicate that entire farms haven't been likely to be benefited evenly from public knowledge stock created by agricultural R&D, in particular high income farms can have enjoyed relatively more benefits of its in terms of efficiency gain. Those can imply agricultural R&D have functioned in the way analogue to digressive subsidies. In addition, the heterogeneous technological needs different among income level farms turns out to be main underlying factors affecting such the skewed benefit distribution of agricultural R&D over different income level farms.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• Journal of Korea Technology Innovation Society
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• v.14 no.2
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• pp.373-404
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• 2011

The purpose of research is to reveal the effect of innovation to enterprises' economic performance. The kind of this study has begun since 1960s and lively progressed then. The fmal theoretical result of the effect of innovation to the performance came positive in compare to the mixed results came out in empirical analysis. There are several reason why empirical results are different to the theoretical results. However the major factor is that of using imperfect statistics and inappropriateness of analysis method. This study used a population (1990~2008) provided from Korean Intellectual Property Office, KIPO for patent and also used a population (1990~2008) provided from Korea Investors Service, KIS for research and development. The contribution of this study is enormous statistical analysis. This study used principal component analysis made innovativeness index for appropriate index sampling, and made effort to minimize the error by using appropriate quantile regression for both to panel analysis and rapidly developed company analysis. Dividing the final results into two parts, the growth and the profit, the effect of technological innovation to the firm's growth is not significant to the panel analysis but heavily significant to the upper 10% of high growth firm. By classifying large company and small and medium enterprise, it is significant to upper 10% of high growth firm for large company and generally significant to small and medium enterprise. But for both lower 10% of low growth firms and 25% of low ranking firms are negatively effected, and for high growth firms larger than the medians are positively effected. Especially for upper 10% of high growth firms are mostly effected. It is more effective to the profitability than the growth. The effect to the profit for every enterprises are not significant, but effected significant to the larger enterprises than 25% of low ranking enterprises especially most effective to the upper 10% of high-profit enterprises. The analysis for the large company, it was significant and positively effected to the upper 10% of high profit enterprises and 25% of low ranking enterprises, but the negatively effected for the low-profit enterprises. For the small and medium enterprises, it is negatively effected for both 10% of low ranking enterprises and 25% of low ranking enterprises. However it is positively effective and significant for the high ranking enterprises than median, especially for those high growth firms. It is meaningful to recognize significancy by quantile, but more implicative result is to finding more effectiveness to the small and medium enterprises than to the large company.

• Smart Structures and Systems
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• v.20 no.1
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• pp.11-22
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• 2017

The long-term effect of ambient temperature on bridge strain is an important and challenging problem. To investigate this issue, one year data of strain and ambient temperature of a long-span cable-stayed bridge is studied in this paper. The measured strain-time history is decomposed into two parts to obtain the strains due to vehicle load and temperature alone. A linear regression model between the temperature and the strain due to temperature is established. It is shown that for every $1^{\circ}C$ increase in temperature, the stress is increased by 0.148 MPa. Furthmore, the extreme value distributions of the strains due to vehicle load, temperature and the combination effect of them during the remaining service period are estimated by the average conditional exceedance rate approach. This approach avoids the problem of declustering of data to ensure independence. The estimated results demonstrate that the 95% quantile of the extreme strain distribution due to temperature is up to $1.488{\times}10^{-4}$ which is 2.38 times larger than that due to vehicle load. The study also indicates that the estimated extreme strain can reflect the long-term effect of temperature on bridge strain state, which has reference significance for the reliability estimation and safety assessment.

• Fisheries and Aquatic Sciences
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• v.23 no.7
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• pp.19.1-19.14
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• 2020

Three generalized additive models were applied to the distribution of anchovy eggs and oceanographic factors to determine the occurrence of anchovy spawning grounds in Korean waters and to identify the indicators of their occurrence using survey data from the spring and summer of 1985, 1995, and 2002. Binomial and Gaussian types of generalized additive models (GAM) and quantile generalized additive models (QGAM) revealed that egg density was influenced mostly by ocean temperature and salinity in spring, and the vertical structure of temperature, salinity, dissolved oxygen, and zooplankton biomass during summer in the upper quantiles of egg density. The GAM and QGAM model deviance explained 18.5-63.2% of the egg distribution in summer in the East and West Sea. For the principle component analysis-based GAMs, the variance explained by the final regression model was 27.3-67.0%, higher than the regular models and QGAMs for egg density in the East and West Sea. By analyzing the distribution of anchovy eggs off the Korean coast, our results revealed the optimal temperature and salinity conditions, in addition to high production and high vertical mixing, as the key indicators of the major spawning grounds of anchovies.

• Journal of Distribution Science
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• v.11 no.7
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• pp.5-13
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• 2013

Purpose - The study explores social well-being of the community of five selected countries of the South Asia: India, Pakistan, Sri Lanka, Nepal and Bangladesh. The study compares effectiveness of macroeconomic policies across the countries through interactive effects of the macroeconomic policy variables with the regional dummy variables. Research design, data, and methodology - Using the data set for the period of 1990-2008, this study employs panel data models, quantile regression methods, and the fixed effects method, which the constant is treated as group or country-specific. The model can also be known as the least-squares dummy variables estimator. Results - The results reveal significant chances of improvement in the well-being of the people while living in India and Pakistan as compared to the other countries of the region where India relatively stands with better chances of providing opportunities to improve the well-being of the people. Conclusions - This study recommends an increasing allocation of budget on education and health in order to enhance social well-being in the South Asian region. Inflation is the main cause of deteriorating well-being of the South Asian community by escalating the cost of living. Comprehensive study is recommended by employing the micro data models in the region.