• Journal of applied mathematics & informatics
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• 제4권2호
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• pp.501-512
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• 1997

In multiple linear regression model we have presupposed assumptions (independence normality variance homogeneity and so on) on error term. When case weights are given because of variance heterogeneity we can estimate efficiently regression parameter using weighted least squares estimator. Unfortunately this estimator is sen-sitive to outliers like ordinary least squares estimator. Thus in this paper we proposed some statistics for detection of outliers in weighted least squares regression.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.355-366
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• 2003

A unified procedure for principal component regression (PCR), partial least squares (PLS) and ordinary least squares (OLS) is proposed. The process gives solutions for PCR, PLS and OLS in a unified and non-iterative way. This enables us to see the interrelationships among the three regression coefficient vectors, and it is seen that the so-called E-matrix in the solution expression plays the key role in differentiating the methods. In addition to setting out the procedure, the paper also supplies a robust numerical algorithm for its implementation, which is used to show how the procedure performs on a real world data set.

• 조명전기설비학회논문지
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• 제21권7호
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• pp.61-67
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• 2007

전력수요예측은 전력계통의 운용을 위해 필수적이다. 따라서 다양한 방법이 제시되어 왔으며, 특히 특수일의 수요예측은 평일과 구분되며, 부하 패턴을 축출하기에 충분한 자료 확보가 어려워 예측 오차가 크게 나타난다. 본 논문에서는 특수일의 부하예측 정확도를 개선하기 위해 퍼지 최소자승 선형회귀 모델을 분석한다. 4종류의 퍼지 최소자승 선형회귀 모델에 대해 분석과 사례연구를 통하여 가장 정확한 모델을 제시한다.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1169-1180
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• 2006

Partial least squares regression (PLS) is a biased, non-least squares regression method and is an alternative to the ordinary least squares regression (OLS) when predictors are highly collinear or predictors outnumber observations. One way to understand the properties of biased regression methods is to know how the estimators shrink the OLS estimator. In this paper, we introduce an expression for the shrinkage factor of PLS and develop a new shrinkage expression, and then prove the equivalence of the two representations. We use two near-infrared (NIR) data sets to show general behavior of the shrinkage and in particular for what eigendirections PLS expands the OLS coefficients.

• Journal of the Korean Data and Information Science Society
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• 제23권2호
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• pp.393-401
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• 2012

This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.651-659
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• 2001

Preference map is a widely used graphical method for the preference data set which is frequently encountered in the field of marketing research. This provides joint configuration usually in two dimensional space between "products" and their "attributes". Whereas the classical preference map adopts the ordinary least squares method in deriving map, the present article suggests the weighted least squares approach providing the better graphical display and interpretation compared to the classical one. Internet search engine data in Korea are analysed for illustration.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.507-518
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• 1995

The ordinary least squares based estiamte $S^2$ of the disturbance variance is considered in the linear regression model when the disturbances follow the first-order moving-average process. It is shown that $S^2$ is weakly consistent estimate for the disturbance varaince without any restriction on the regressor matrix X. Also, simple exact bounds on the relative bias of $S^2$ are given in finite sample sizes.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.229-234
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• 2022

The study aims to investigate whether Musharakah management has an impact on Chinese and Malaysian business partnerships. To estimate the relationship between Musharakah and the Sino-Malaysian partnership, this study uses a panel econometric technique namely pooled ordinary least squares. Ordinary Least Squares regression (OLS) is a common technique for estimating coefficients of linear regression equations which describe the relationship between one or more independent quantitative variables and a dependent variable. Data was retrieved from the annual reports (from 2009 to 2019) of non-financial firms listed on the stock exchange of China and Malaysia. Four partnership measures (i.e., Musharakah, Mudarabah, Tawuruq, and Kafalah) were used to estimate the impact of Musharakah on the Sino-Malaysian partnership. Empirical results reveal that Musharakah and Mudarabah are positively related to Kafalah but the relationship is statistically insignificant. Alternatively, Musharakah is positively and significantly related to Mudarabah. Musharakah and Mudarabah have a positive but insignificant relationship. The findings of this study suggest that management of partnership has a positive impact on firm partnership. Furthermore, it supports the hypothesis that improving partnership enhances Musharakah, which has a positive impact on the firm's partnership.

• Communications for Statistical Applications and Methods
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• 제4권2호
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• pp.353-358
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• 1997

When the disturbances in the linear repression medel are generated by a seasonal autoregressive scheme the Cochrane Orcutt transformation estimator (COTE) is a well known alternative to Generalized Least Squares estimator (GLSE). In this paper it is analyzed in which situation the Ordinary Least Squares estimator (OLSE) is always better than COTE for positive autocorrelation in terms of efficiency which is here defined as the ratio of the total variances.

• 대한토목학회논문집
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• 제6권4호
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• pp.43-52
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• 1986

computer의 활용이 증대됨에 따라 각종 자료의 회귀분석에 최소자승법이 널리 사용되고 있다. computer의 유효자리수에 따른 회귀계수의 불안정성과 표준최소자승법의 문제점을 기술하고, 이를 개선시키는 방안으로 직교함수를 이용한 최소자승법을 사용하였다. 또한 위의 두가지 방법의 결과를 수치검정예를 통하여 비교 분석하였으며 직교함수를 재직교화하여 정밀도를 향상시키는 기법도 다루었다. 적용예로 AR 과정의 적정차수를 결정하는 Akaike의 FPE(final prediction error)를 이용하여 평창관측소의 월유량 시계열의 AR 과정 적정차수를 구하였으며, AR(2)가 적합한 것으로 선정되었다.