• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.167-175
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• 2003

In this paper we develop a robust procedure to estimate regression coefficients for a linear model with censored and truncated data based on simplicial regression depth. Simplicial depth of a point is defined as the proportion of data simplices containing it. This simplicial depth can be extended to regression problem with censored and truncated data. Any line can be given a depth and the deepest regression line is the line with the maximum simplicial regression depth. We show how the proposed regression performs through analyzing AIDS incubation data.

• Restorative Dentistry and Endodontics
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• 제43권3호
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• pp.34.1-34.5
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• 2018

In the previous section, we established a simple linear regression line by finding the slope and intercept using the least square method as: ${\hat{Y}}=30.79+0.71X$. Finding the regression line was a mathematical procedure. After that we need to evaluate the usefulness or effectiveness of the regression line, whether the regression model helps explain the variability of the dependent variable. Also, statistical inference of the regression line is required to make a conclusion at the population level, because practically, we work with a sample, which is a small part of population. Basic assumption of sampling method is simple random sampling.

• 소프트웨어공학소사이어티 논문지
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• 제29권2호
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• pp.1-6
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• 2020

소프트웨어 제품라인 개발은 제품군의 개발을 위하여 공통적인 부분과 가변적인 부분을 분리 개발함으로써 중복개발을 피하여 효율적으로 제품군을 개발하는 개발 패러다임이다. 소프트웨어 제품라인 개발에서 제품군을 생성하기 위해 사용되는 소스코드를 제품라인 코드 베이스라고 부르고, 제품라인 코드 베이스가 변경되어 제품군의 제품들이 영향을 받을 때 영향 받은 제품들을 시험하는 활동을 제품라인 회귀시험이라고 한다. 이 때 제품군의 각 제품을 개별적으로 시험하는 대신, 변경과 무관한 시험을 파악하여 피할 수 있다면 효율적인 제품라인 회귀시험이 가능해 질 것이다. 본 논문은 이런 방법으로 소프트웨어 제품라인 회귀시험을 효율적으로 수행하는 자동화된 방법인 SRTS를 소개한다. 이 방법은, 먼저 제품라인 코드 베이스와 시험 항목을 공통성과 가변성을 기반으로 나누고 변경에 영향을 받는 시험 항목을 식별하여 선택한 후, 선택된 시험 항목만을 재실행함으로써 불필요한 시험을 줄인다.

• 한국컴퓨터정보학회논문지
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• 제20권12호
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• pp.29-36
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• 2015

In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.

• 한국임상수의학회지
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• 제27권4호
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• pp.427-434
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• 2010

Correlation is a technique used to measure the strength or the degree of closeness of the linear association between two quantitative variables. Common misuses of this technique are highlighted. Linear regression is a technique used to identify a relationship between two continuous variables in mathematical equations, which could be used for comparison or estimation purposes. Specifically, regression analysis can provide answers for questions such as how much does one variable change for a given change in the other, how accurately can the value of one variable be predicted from the knowledge of the other. Regression does not give any indication of how good the association is while correlation provides a measure of how well a least-squares regression line fits the given set of data. The better the correlation, the closer the data points are to the regression line. In this tutorial article, the process of obtaining a linear regression relationship for a given set of bivariate data was described. The least square method to obtain the line which minimizes the total error between the data points and the regression line was employed and illustrated. The coefficient of determination, the ratio of the explained variation of the values of the independent variable to total variation, was described. Finally, the process of calculating confidence and prediction interval was reviewed and demonstrated.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.137-141
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• 2003

LS-SVM(least squares support vector machine) is a widely applicable and useful machine learning technique for classification and regression analysis. LS-SVM can be a good substitute for statistical method but computational difficulties are still remained to operate the inversion of matrix of huge data set. In modern information society, we can easily get huge data sets by on line or batch mode. For these kind of huge data sets, we suggest an on line pruning regression method by LS-SVM. With relatively small number of pruned support vectors, we can have almost same performance as regression with full data set.

• 품질경영학회지
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• 제38권3호
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• pp.354-362
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• 2010

This paper presents a non-linear control chart based on support vector machine regression (SVM-R) to improve the accuracy of fault detection of cyclic signals. The proposed algorithm consists of the following two steps. First, the center line of the control chart is constructed by using SVM-R. Second, we calculate control limits by variances that are estimated by perpendicular and normal line of the center line. For performance evaluation, we apply proposed algorithm to the industrial data of the chemical vapor deposition process which is one of the semiconductor processes. The proposed method has better fault detection performance than other existing method

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.10-11
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• 2006

The fault location is obtained from the distance relay that detects the fault of the transmission line. In this time, transmission line crews track down the fault location and the reasons. However, because of having error at the fault location of the distance relay, there is a discordance between real and obtained fault location. As this reason, the inspection time for finding fault location can be longer. In this paper, we proposed the statistical (regression) analysis method based on each type of relay's the historical fault location data and the real fault distance data to improve the problems. With finding the regression equation based on the regression analysis, and putting the relay fault location into that equation, the real fault distance is calculated. As a result of the Prediction fault location, the inspection time of transmission line can be reduced.

• 대한음성학회지:말소리
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• 제66호
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• pp.21-39
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• 2008

The purpose of this study is to analyze the intonational slope characteristics of the Korean news utterances. Prosodic phrases were analyzed in terms of the K-ToBI labeling system. In addition, the change of intonation contour that occurs throughout the sentences was discussed in terms of types of media and gender. Results showed that the overall declination of the intonation contour of radio and male revealed a gentler slope than that of TV and female, respectively. While the regression of the top line slope showed male's higher $R^2$ with the number of words, the base line slope of the radio and female was proved to be highly influenced from the number of syllables, words, and prosodic phrases. A lot more independent variables statistically affected to the base line slope. This means that the base line slope was strongly related to the variables, the top line slope, otherwise, could be more freely fluctuated due to the light correlation with them.

• 한국위성정보통신학회논문지
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• 제12권2호
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• pp.42-45
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• 2017

전력선통신 시스템에서는 전력망을 활용한 통신 방식을 사용하기 때문에 일반적 통신선로를 활용한 통신 방식에 비해 잡음이 많고, 이것으로 인한 성능 저하가 문제가 되고 있다. 이러한 잡음으로 인한 성능 저하를 완화시키기 위해, 본 논문에서는 전력선통신 시스템에서의 임펄스 잡음 환경에서 신호를 검출하는 인공지능 알고리즘을 제안한다. 다항식 회귀법을 이용하여 임펄스 잡음 신호의 원신호를 예측하고, 시뮬레이션 결과를 통해 본 논문에서 제안한 인공지능 알고리즘을 적용한 전력선통신 시스템에서 임펄스 잡음 환경내 신호 검출 성능 향상을 입증한다.