• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.5
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• pp.465-475
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• 2020

I-D-F curves were induced by Box-Cox transformation using rainfall data from five major cities in Korea: Seoul, Busan, Daegu, Daejeon, and Gwangju, as well as from Sancheong (South Gyeongsang province) and Yeongcheon (North Gyeongsang province) stations. The practicality of the Box-Cox transformation is more scalable than the traditional method of frequency analysis in terms of applicability because it is available even if the analysis data are insufficient to perform general frequency analysis and do not produce an appropriate probability density function. For the case in which rainfall data for the entire period (10-1440 minutes) and short-term period (20, 30, 40, 50 minutes) at the foregoing 7 stations are omitted, there was a relative error of -23.0 % to 14.7 % at a duration of 10 to 60 minutes below the 100-year frequency. Accordingly, rainfall analysis requires inducing I-D-F curves, including for the short term (20, 30, 40, 50 minutes), and if rainfall data are omitted for the short term (20, 30, 40, 50 minutes), it is necessary to increase the existing margin rate depending on the point in order to ensure the safe design of small-scale hydraulic structures.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.510-512
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• 2003

본 논문에서는 문서의 자동 분류를 위한 용어 빈도 가중치 계산 방법으로 Box-Cox변환기법을 응용한 정규화 용어빈도 가중치를 정의하고, 이를 문서 분류에 적응하였다. 여기서 Box-Cox 변환기법이란 자료를 정규분포화 할 때 적용하는 통계적인 변환방법으로서, 본 논문에서는 이를 응용하여 새로운 용어빈도가중치 계산법을 제안한다. 문서에서 등장한 용어 빈도는 너무 많거나 적게 등장할 경우, 중요도가 떨어지게 되는데, 이는 용어의 중요도가 빈도에 따른 정규분포로 모델링 될 수 있다는 것을 의미한다. 또한 정규화 가중치 계산방법은 기존의 용어빈도 가중치 공식과 비교할 때, 용어마다 계산방법이 달라져, 로그나 루트와 같은 고정된 가중치 방법보다는 좀더 일반적인 방법이라 할 수 있다. 신문기사 8000건을 대상으로 4개의 그룹으로 나누어 실험 한 결과, 정규화 용어빈도가중치 계산방법이 모두 우위의 분류 정확도롤 가져, 본 논문에서 제안한 방법이 타당함을 알 수 있다.

• Environmental and Resource Economics Review
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• v.5 no.2
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• pp.291-302
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• 1996

환경질 개선의 편익추정에 사용되는 헤도닉 가격모형에서 제1단계 헤도닉 함수 추정시 그 함수형태에 따라 결과가 편의를 가질 수 있다. 본 논문에서는 13가지의 각기 다른 비선형 및 선형 헤도닉 함수 등을 한국 주택시장에 적용하여 그 적합성을 이론 및 실증적 방법을 병행하여 검증하였다. 그 결과, 고전적으로 종속변수만을 변환시키는 Box-Cox 함수형태나 Box-Cox 변형계수가 사전적으로 0과 1사이에 있음을 가정하는 오목한(concave) 한 함수형태가 기존 연구와는 달리 한국시장에는 적합한 함수형태가 아니라는 결과를 이끌어 냈다. 나아가 서울 주택시장에 가장 적합한 함수형태는 종속 및 독립변수를 각각 다르게 변환시키는 헤도닉 함수형태임을 보여 주었다. 아울러 본 연구는 간접적으로 헤도닉 가격모형 적용시 그 지역의 주택시장 특성에 관한 연구가 선행되어야 함을 시사하고 있다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.18-27
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• 2019

The process control methods based on the statistical analysis apply the analysis method or mathematical model under the assumption that the process characteristic is normally distributed. However, the distribution of data collected by the automatic measurement system in real time is often not followed by normal distribution. As the statistical analysis tools, the process capability index (PCI) has been used a lot as a measure of process capability analysis in the production site. However, PCI has been usually used without checking the normality test for the process data. Even though the normality assumption is violated, if the analysis method under the assumption of the normal distribution is performed, this will be an incorrect result and take a wrong action. When the normality assumption is violated, we can transform the non-normal data into the normal data by using an appropriate normal transformation method. There are various methods of the normal transformation. In this paper, we consider the Box-Cox transformation among them. Hence, the purpose of the study is to expand the analysis method for the multivariate process capability index using Box-Cox transformation. This study proposes the multivariate process capability index to be able to use according to both methodologies whether data is normally distributed or not. Through the computational examples, we compare and discuss the multivariate process capability index between before and after Box-Cox transformation when the process data is not normally distributed.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.535-555
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• 2021

This study empirically analyzes the effects of international oil prices on domestic stock market volatility. The data used for the analysis are 10-minute high-frequency data of the KOSPI index and WTI futures price from January 2, 2015, to July 30, 2021. For using the high-frequency data, a heterogeneous autoregression (HAR) model is employed. The analysis model utilizes the advantages of high frequency data to observe the impact of international oil prices through realized volatility, realized skewness, and kurtosis as well as oil price return. In the estimation, the Box-Cox transformation is applied in consideration of the distribution of realized volatility with high skewness. As a result, it finds that the daily return fluctuation of the WTI price has a statistically significant positive (+) effect on the volatility of the KOSPI return. However, the volatility, skewness, and kurtosis of the WTI return do not appear to affect the volatility of the KOSPI return. This result is believed to be because the volatility of the KOSPI return reflects the daily change in the WTI return, but does not reflect the intraday trading behavior of investors.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.100-102
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• 2022

데이터의 품질을 파악하고 그 기준을 선정하는 것은 해양 항로 표지와 같은 분석에 있어서 중요한 역할을 한다. 본 연구에서는 해양 분야에서 디지털 항로표지 데이터의 품질 진단을 위해 공정능력지수를 이용하여 데이터의 품질을 정량적으로 산출하고 그 결과에 대한 판정 기준을 명확히 하여 데이터에 대한 품질을 판단할 수 있는 척도를 제시하였다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.33-39
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• 2013

In the transformation of response variable in partial linear models outliers can cause a bad effect on estimating the transformation parameter, just as in the linear models. To solve this problem the processes of estimating transformation parameter and detecting outliers are needed, but have difficulties to be performed due to the arbitrariness of the nonparametric function included in the partial linear model. In this study, through the estimation of nonparametric function and outlier detection methods such as a sequential test and a maximum trimmed likelihood estimation, processes for transforming response variable robust to outliers in partial linear models are suggested. The proposed methods are verified and compared their effectiveness by simulation study and examples.

• Journal of the Korean GEO-environmental Society
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• v.10 no.7
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• pp.7-14
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• 2009

The correlation equation empirically proposed to obtain compression indexes has been proposed to conveniently obtain the value using the soil parameter that can be obtained through simple tests when the number of time of consolidation testing is low or the distribution is large but most of the analyzed regions are limited to certain regions abroad or in the country and multiple data were integrated for use in many cases, thus it is not very reasonable to apply it. Therefore, to establish a new design method considering the uncertainty of the ground, it was selected the Kwangyang port area of which the data have been collected recently thus are relatively more reliable as the subject region of the study in order to maximally reduce the uncertainty of test data. After performing the verification of the normality of the consolidation test data obtained from the selected region and the transformation of variables, a prediction formula was proposed through the regression model with the transformed variables and the proposed regression model with transformed variables was compared with existing empirical equations to verify the suitability of the proposed model formula. After analyzing, it was confirmed that the coefficient of determination was increased after the Box-Cox variable transformation, thus the explanatory power was being enhanced and through the root-mean-square-error method, it was confirmed that the proposed model formula showed the most closed value to the test value.

• Convergence Security Journal
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• v.7 no.2
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• pp.49-55
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• 2007

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. From the subdivision of this analysis, new attemp needs the side of the quality control. In this paper, we discuss process capability analysis using process capability indexs. Because of software failure interval time is pattern of nonnegative value, instead of capability analysis of suppose to normal distribution, capability analysis of process distribution using to Box-Cox transformation is attermpted. The used software failure time data for capability analysis of process is SS3, the result of analysis listed on this chapter 4 and 5. The practical use is presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.52-64
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• 2023

This paper concentrated on estimating the travel time value of individual regional bus passengers in various in-vehicle crowding conditions. In the analysis model, the traffic-selection data of individual transportation passengers based on smart-card data were used. Variables which reflect the level of in-vehicle crowding and the variables of in-vehicle travel time that reflect the level of in-vehicle crowding were included in the model using Box-Cox transformation. The result of this paper indicates that the travel time value experienced by individual users would increase as the in-vehicle crowding level increases. The smart card data used in this paper is considered to have significant implications in terms of conducting more sophisticated and realistic qualitative research to reflect the values of variables for in-vehicle traffic hours and in-vehicle crowding levels, which previously had limitations in observation and quantification. It is expected that the effects of improvement measures for reducing congestion on regional buses can be considered quantitatively by applying the estimation results of crowding multiplier.