• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.367-379
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• 2012

야구경기에서 순위를 예측하는 것은 야구팬들에게 관심의 대상이 된다. 이러한 순위를 예측하기 위해서 2011년 한국프로야구 기록 자료를 바탕으로 산술평균방법, 가중평균방법, 주성분분석방법, 주성분회귀분석 방법을 제시한다. 표준화를 통한 산술평균, 상관계수를 이용한 가중평균과 주성분 분석을 이용해서 순위를 예측하고, 최종모형으로 주성분회귀분석 모형이 선택되었다. 주성분 분석으로 축약된 변수를 이용해서 회귀분석을 실시하여, 투수부분, 타자부분, 투수와 타자부분의 순위예측 모형을 제안한다. 예측된 회귀모형을 통해서 2012년도 순위 예측이 가능하다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2010년도 춘계학술대회
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• pp.402-408
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• 2010

Forecasting have qualitative and quantitative methods. Quantitative one analyze macro-economic factors such as the rate of exchange, oil price, interest rate and also predict the micro-economic factors such as sales and demands. Applying various statistical methods depends on the type of data. when data has seasonality and trend, Time Series analysis is proper but when it has casual relation, Regression analysis is good for this. Time Series and Regression can be used together. This study investigate artificial neural networks which is predictive technique for casual relation and try to compare the accuracy of forecasting between regression analysis and artificial neural network.

• Communications for Statistical Applications and Methods
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• 제1권1호
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• pp.102-111
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• 1994

We Propose a method of sensitivity analysis in latent root regression analysis (LRRA). For this purpose we derive the quantities ${\beta\limits^\wedge \;_{LRR}}^{(1)}$, which correspond to the theoretical influence function $I(x, y \;;\;\beta\limits^\wedge \;_{LRR})$ for the regression coefficient ${\beta\limits^\wedge}_{LRR}$ based on LRRA. We give a numerical example for illustration and also investigate numerically the relationship between the estimated values of ${\beta\limits^\wedge \;_{LRR}}^{(1)}$ with the values of the other measures called sample influence curve(SIC) based on the recomputation for the data with a single observation deleted. We also discuss the comparision among the results of LRRA, ordinary least square regression analysis (OLSRA) and ridge regression analysis(RRA).

• 품질경영학회지
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• 제29권3호
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• pp.124-137
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• 2001

In general, it is very efficient and effective to use screening variables that are correlated with the performance variable in case that measuring the performance variable is impossible (destructive) or expensive. The general methodology for searching surrogate variables is regression analysis. This paper considers the inspection problem in CRT (Cathode Ray Tube) production line, in which the performance variable (dependent variable) is binary type and screening variables are continuous. The general regression with dummy variable, discriminant analysis and binary logistic regression are considered. The cost model is also formulated to determine economically inspection procedure with screening variables.

• Archives of Pharmacal Research
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• 제11권1호
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• pp.45-51
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• 1988

The feature of resolution enhancement by derivative operation is linked to one of the multivariate analysis, which is multiple linear regression with two options, all possible and stepwise regression. Examined samples were synthetic mixtures of 5 vitamins, thiamine mononitrate, riboflavin phosphate, nicotinamide, pyridoxine hydrochloride and ascorbic acid. All components in mixture were quantified with reasonably good accuracy and precision. Whole data processing procedure was accomplished on-line by the development of three computer programs written in APPLESOFT BASIC language.

• 융합정보논문지
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• 제9권6호
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• pp.1-6
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• 2019

본 연구에서는 다항식 회귀분석(Polynomial regression analysis) 방법을 이용하여 비선형 특성을 갖는 전자저울의 질량 추정 모델 개발이 이루어 졌다. 전자저울에 사용되는 로드셀의 출력 단자 전압을 기준 질량 추를 사용하여 직접 측정하였고 이 데이터를 이용하여 MS Office 엑셀의 행렬식 계산과 데이터 추세선 분석 기능을 이용하여 다항식 회귀모델을 구하였다. 5kg까지 측정 가능한 로드셀 전자저울을 사용하여 100g단위로 질량을 측정하였고 다항식 회귀분석(Multiple regression analysis) 모델을 구하였으며, 단순(1차), 2차, 3차 다항식 회귀분석에 대한 오차를 구하였다. 각 모델에 대한 회귀 방정식의 적합도 분석을 위해 결정계수(Coefficient of determination)를 제시하여 추정 질량과 측정 데이터와의 상관관계를 나타내었다. 본 연구에서 제안하는 3차 다항식 모델을 이용하여 추정 값의 표준편차가 10g, 결정계수 1.0으로 상당히 정확한 모델을 얻었다. 본 연구에 사용된 선형 회귀 분석 이론을 바탕으로 최근 인공지능 분야에서 많이 사용되고 있는 로지스틱 회귀 분석(Logistic regression analysis)을 활용하여 기상예측, 신약개발, 경제지표 분석 등의 분야에 대한 다양한 연구를 수행할 수 있을 것으로 생각된다.

• 한국해양공학회지
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• 제23권6호
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• pp.71-76
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• 2009

This paper describes a statistical analysis method for predicting a coast fishing boat's effective horsepower. The EHP estimation method for small coast fishing boats was developed, based on a statistical regression analysis of model test results in a circulating water channel. The statistical regression formula of a fishing boat's effective horsepower is determined from the regression analysis of the resistance test results for 15 actual coast fishing boats. This method was applied to the effective horsepower prediction of a G/T 4 ton class coast fishing boat. From the estimation of the effective horsepower using this regression formula and the experimental model test of the G/T 4 ton class coast fishing boat, the estimation accuracy was verified under 10 percent of the design speed. However, the effective horsepower prediction method for coast fishing boats using the regression formula will be used at the initial design and hull-form development stage.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.609-617
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• 2006

A new fuzzy c-regression algorithm for switching regression analysis is presented, which combines fuzzy c-means clustering and least squares support vector machine. This algorithm can detect outliers in switching regression models while yielding the simultaneous estimates of the associated parameters together with a fuzzy c-partitions of data. It can be employed for the model-free nonlinear regression which does not assume the underlying form of the regression function. We illustrate the new approach with some numerical examples that show how it can be used to fit switching regression models to almost all types of mixed data.

• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.205-215
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• 2021

Sufficient dimension reduction is useful dimension reduction tool in regression, and sliced inverse regression (Li, 1991) is one of the most popular sufficient dimension reduction methodologies. In spite of its popularity, it is known to be sensitive to the number of slices. To overcome this shortcoming, the so-called fused sliced inverse regression is proposed by Cook and Zhang (2014). Unfortunately, the two existing methods do not have the direction application to large p-small n regression, in which the dimension reduction is desperately needed. In this paper, we newly propose seeded sliced inverse regression and seeded fused sliced inverse regression to overcome this deficit by adopting iterative projection approach (Cook et al., 2007). Numerical studies are presented to study their asymptotic estimation behaviors, and real data analysis confirms their practical usefulness in high-dimensional data analysis.

• 디지털융복합연구
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• 제18권12호
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• pp.481-488
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• 2020

기호적 회귀분석 (Symbolic Regression)은 회귀분석에서 주어진 데이터에 대하여 종속변수와 독립변수들 사이의 관계를 설명할 수 있는 함수를 직접 생성하는 분석방법으로서 Genetic Programming 이 본 분야의 연구에 가장 선도적으로 적용되고 있으며, 고정된 모델로부터 매개변수들의 최적화를 추구하는 다른 회귀분석 알고리즘들에 비하여 해석이 가능한 모델을 직접 도출할 수 있다는 장점을 갖는다. 본 연구에서는 Coarse grained 병렬 모델에 기반한 Parellel Genetic Programming 을 이용한 symbolic regression 알고리즘을 제시하고 제시된 알고리즘을 PMLB 데이타에 적용하여 해당 알고리즘의 효용성을 분석하고자 한다.