• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.407-416
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• 2016

The purpose of this study is to develop regional regression models to estimate mean low flow for ungauged basins. The unregulated streamflow data observed at 12 multipurpose dams and 4 irrigation dams were analyzed for determining mean low flows. Various types of regression models were developed using the relationship between mean low flows and various sets of watershed characteristics such as drainage area, average slope, drainage density, mean annual precipitation, runoff curve number. The performance of each regression model for estimating mean low flows was assessed by comparison with the results obtained from the observed data. It was found that a regional regression model explained by drainage area, the mean annual precipitation, and runoff curve number showed the best performance. The regression model presented in this study also gives better estimates of mean low flow than the estimates by the drainage-area ratio method and the previous regression model.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.541-546
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• 2002

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.573-585
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• 2018

In this study, we fit the logistic regression model and naïve Bayesian classifier model using 11 risk factors to predict the incidence rate probability for type 2 diabetes mellitus. We then introduce how to construct a nomogram that can help people visually understand it. We use data from the 2013-2015 Korean National Health and Nutrition Examination Survey (KNHANES). We take 3 interactions in the logistic regression model to improve the quality of the analysis and facilitate the application of the left-aligned method to the Bayesian nomogram. Finally, we compare the two nomograms and examine their utility. Then we verify the nomogram using the ROC curve.

• Phonetics and Speech Sciences
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• v.9 no.3
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• pp.17-23
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• 2017

The present study investigates the effect of Accentual Phrase on F0 using a subset of large-scale corpus of Seoul Korean. Four syllable words which were neither preceded nor followed by silent pauses were presumed to be canonical exemplars of Accentual Phrases in Korean. These four syllable words were extracted from female speakers' speech samples. Growth curve analyses, combination of regression and polynomial curve fitting, were applied to the four syllable words. Four syllable words were divided into four groups depending on the categorical status of the initial segment: voiceless obstruents, voiced obstruents, sonorants, and vowels. Results of growth curve analyses indicate that initial segment types have an effect on the F0 (in semitone) in the nucleus of the initial syllable, and the cubic polynomial term revealed that some of the medial low tones in the 4 syllable words may be guided by the principle of contrast maximization, while others may be governed by the principle of ease of articulation.

• Journal of Korean Society of Water and Wastewater
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• v.17 no.4
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• pp.495-502
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• 2003

In order to modify incorrect flow data in the sewage system, the method using the stage-discharge relation and hydraulic characteristic curve of sewer pipe are applied. The modified data were verified with field measured data and the infiltration analysis using the modified data was carried out. When flowrate were measured using the flow-meter in fair weather, the stage data were comparatively consistent but velocity data were very poor for the most part. Therefore, it was recommended that sewage flowrate variation characteristic curve and infiltration were computed using the modified data on the basis of stage data. Especially, in the case of using the hydraulic characteristic curve, extrapolation results of the rainy season flowrate using regression curve on the basis of the data in fair weather were also reasonable.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.363-374
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• 2008

Intensity-Duration-Frequency (IDF) curve that is essential to calculate rainfall quantiles for designing hydraulic structures in Korea is generally formulated by regression analysis. In this study, IDF curve derived by the cumulative distribution function ("IDF by CDF") of the proper probability distribution function (PDF) of each site is suggested, and the corresponding parameters of IDF curve are computed using genetic algorithm (GA). For this purpose, IDF by CDF and the conventional IDF derived by regression analysis ("IDF by REG") were computed for 22 Korea Meteorological Administration (KMA) rainfall recording sites. Comparisons of RMSE (root mean squared error) and RRMSE (Relative RMSE) of rainfall intensities computed from IDF by CDF and IDF by REG show that IDF by CDF is more accurate than IDF by REG. In order to accommodate the effect of the recent intensive rainfall of Korea, the rainfall intensities computed by the two IDF curves are compared with that by at-site frequency analysis using the rainfall data recorded by 2006, and the result from IDF by CDF show the better performance than that from IDF by REG. As a result, it can be said that the suggested IDF by CDF curve would be the more efficient IDF curve than that computed by regression analysis and could be applied for Korean rainfall data.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.339-351
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• 2017

Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient; however, many authors have shown that an analysis of the Gini coefficient and its corresponding variance can be obtained from a regression model. Despite the simplicity of the regression approach method to compute a standard error for the Gini coefficient, the use of the proposed regression model has been challenging in economics. Therefore in this paper, we focus on a comparative study among the regression approach and resampling techniques. The regression method is shown to overestimate the standard error of the Gini index. The simulations show that the Gini estimator based on the modified regression model is also consistent and asymptotically normal with less divergence from normal distribution than other resampling techniques.

• Journal of Korean Society for Quality Management
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• v.25 no.4
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• pp.106-114
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• 1997

The smoothing parameter or bandwidth is crucial to performance of the kernel based regression estimator. So the choice of a "optimal" smoothing parameter produce a single curve estimate. If a single estimate is replaced by a family of estimates, it become easy that we understand what varies with choice of the smoothing parameter. This paper suggests the threshold of the maximum bandwidth and the number of the family members in the regression context.n context.

• Korean Journal of Remote Sensing
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• v.6 no.2
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• pp.153-164
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• 1990

A statistical correlation between cloud thickness and brightness is shown by regression analysis using the least-square method. Cloud thicknesses are obtained from radiosonde observation. Brightness values are obtained from GMS visible channel. Regression analyses are preformed on both thickness data used in conjunction with brightness data for summer season. The results are shown by the regression curve relating thickness and brightness accounting for 79% of variance. And the relationship between thickness and precipitable water in the cloud layers is analyzed. The thickness shows a positive correlation with precipitable water in cloudy layers.

• Journal of Biomedical Engineering Research
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• v.35 no.6
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• pp.227-233
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• 2014

In this paper, to quantitatively evaluate the degree of rehabilitation for the disabled of unilateral lower extremity, we compared the EMG pattern of normal and simulated abnormal gait. The EMG signal was measured at a rate of 1 kHz on the quadriceps and biceps femoris, the pressure sensor was attached to the sole in order to distinguish the gait cycle. Integrated EMG (IEMG) was obtained by the gait cycle, and classified four patterns that were the normal gait pattern, amplitude decrease pattern, reversed pattern, and irregular pattern. For comparison of the patterns, a curve fitting was performed using the trigonometric functions. The result of curve fitting, the method using a variable A that corresponds to the amplitude of the regression curve was able to distinguish the reverse pattern and remaining pattern. The coefficient of determination ($R^2$) representing coincidence of the pattern of the regression curve and EMG was confirmed the biggest value at the normal gait. Therefore, the degree of normal gait can be confirmed using the coefficient of determination. This results show that it is possible to quantitatively confirm the degree of unilateral lower extremity disabled rehabilitation, and it will be contributed to the study of efficient rehabilitation methods by objective analysis.