• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.277-285
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• 1998

The smoothing parameter $\lambda$ in smoothing spline regression is usually selected by minimizing cross-validation (CV) or generalized cross-validation (GCV). But, simple CV or GCV is poor candidate for estimating prediction error. We defined MGCV (Multifold Generalized Cross-validation) as a criterion for selecting smoothing parameter in smoothing spline regression. This is a version of cross-validation using $leave-\kappa-out$ method. Some numerical results comparing MGCV and GCV are done.

• Journal of the Korean Data and Information Science Society
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• 제9권1호
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• pp.77-88
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• 1998

Smoothing spline estimators are modified to remove boundary bias effects using the technique proposed in Eubank and Speckman (1991). An O(n) algorithm is developed for the computation of the resulting estimator as well as associated generalized cross-validation criteria, etc. The asymptotic properties of the estimator are studied for the case of a linear smoothing spline and the upper bound for the average mean squared error of the estimator given in Eubank and Speckman (1991) is shown to be asymptotically sharp in this case.

• International Journal of Automotive Technology
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• 제8권1호
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• pp.59-66
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• 2007

High frequency excitation terms in a cam profile can excite vibration of a cam follower system. In this paper, modified smoothing spline curves are used to reduce the high frequency terms. The essential difference between the proposed method and other existing approaches is its ability to make the principal cam motions smooth while still exactly satisfying boundary conditions of follower displacement, velocity and acceleration. The boundary values usually depend on the ramp properties of a cam. Our method, thus, allows designers to smooth the existing cam motion without any damages on its ramp areas. Because the ramp height, velocity and acceleration are maintained exactly, more radical smoothing is possible. An example shows that the proposed method can be a powerful tool of cam profile smoothing, which removes high frequency components in the cam profile excitations without any changes in ramp properties.

• Journal of the Korean Data and Information Science Society
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• 제6권1호
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• pp.63-71
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• 1995

We have consider the study of local influence for smoothing parameter estimates in spline regression model with heteroscedasticity. Practically, generalized cross-validation does not work well in the presence of heteroscedasticity. Thus we have proposed the local influence measure for generalized cross-validation estimates when errors are heteroscedastic. And we have examined effects of diagnostic by above measures through Hyperinflation data.

• Journal of the Korean Statistical Society
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• 제30권4호
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• pp.645-660
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• 2001

In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

• 대한의용생체공학회:의공학회지
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• 제22권4호
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• pp.311-319
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• 2001

Statistical reconstruction methods in the context of a Bayesian framework have played an important role in emission tomography since they allow to incorporate a priori information into the reconstruction algorithm. Given the ill-posed nature of tomographic inversion and the poor quality of projection data, the Bayesian approach uses regularizers to stabilize solutions by incorporating suitable prior models. In this work we show that, while the quantitative performance of the standard filtered backprojection (FBP) algorithm is not as good as that of Bayesian methods, the application of spline-regularized smoothing to the sinogram space can make the FBP algorithm improve its performance by inheriting the advantages of using the spline priors in Bayesian methods. We first show how to implement the spline-regularized smoothing filter by deriving mathematical relationship between the regularization and the lowpass filtering. We then compare quantitative performance of our new FBP algorithms using the quantitation of bias/variance and the total squared error (TSE) measured over noise trials. Our numerical results show that the second-order spline filter applied to FBP yields the best results in terms of TSE among the three different spline orders considered in our experiments.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권2호
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• pp.78-89
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• 2016

Purpose: In this paper, we investigate whether the endeavors for Six Sigma quality management by a firm have positive effects on its financial performance and the length of Six Sigma implemented period affects its financial status. We find a relationship between Six Sigma implemented period and several financial performance index using a smoothing spline function. Methods: A smoothing spline function is used in order to analyze the relationship between efforts for quality management and financial performance. Specifically, the return on assets, return on equity, sales cost and business fee are investigated as dependent variables and the efforts for quality management as independent variable. Results: As a result of the analysis, the indication is that companies that put effects into the Six Sigma quality management have a positive result in its financial status. In detail, the efforts for Six Sigma quality management have positive effects on total asset turnover ratio and Six Sigma implemented period on net income to net sales ratio. Additionally, companies with longer (shorter) period of Six Sigma program have more (less) improvement in its financial status. Conclusion: It can be concluded that the company's efforts for quality management positively influence financial performance.

• 응용통계연구
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• 제13권2호
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• pp.371-381
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• 2000

비모수 회귀모형에 있어서 평활스플라인에 대하여 언급하고, 그 간단한 성질을 다룬다. 선형회귀나 다항식회귀에서는 적합하기 나쁜 데이터가 많이 존재한다. 설명변수가 여러 개인 경우에 준모수 회귀모형은 하나 혹은 그 이상의 변수에 대해서는 비모수 함수를 다른 변수에 대하서는 선형함수를 적합시켜 그들의 가법성을 가정한 것이다. 준모수 회귀모형에 있어서 선형부분의 회귀계수의 추정량에 편의가 발생하고, 여기서는 그 편의에 대한 점근 정규성을 다룬다

• Journal of the Korean Data and Information Science Society
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• 제7권2호
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• pp.257-262
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• 1996

본 논문은 스플라인 희귀모형에서 평활모수를 추정할 때 사전 작업으로 영향력 진단을 하는 문제를 다룬다. 평활모수의 추정방법으로 일반화최대우도함수법을 사용할 때, 얻어지는 추정 치에 영향을 주는 관측치를 진단하는 측도를 제안하고, 찾아낸 영향력 관측치를 수정하여 올바른 평활모수 추정치를 찾는 방법을 소개한다.

• 한국통신학회논문지
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• 제42권1호
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• pp.162-171
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• 2017

심전도 신호에 있는 저주파 잡음 성분은 기저선 변동을 일으킨다. 본 논문에서는 기저선 변동이 있는 심전도 신호에 대하여 형태학 연산과 평활화 스플라인 연산을 사용하여 기저선 변동 잡음을 제거하였다. 형태학 연산만 이용하여 기저선 변동 잡음을 제거하는 경우, 사용한 구조요소에 따라 원 신호의 특징점 정보를 손상시킬 수 있다. 형태학 연산의 단점을 해결하기 위하여, 형태학 연산 후 평활화 스플라인 연산을 적용하였다. ECG 신호 처리를 위한 기존의 형태학 연산을 이용한 방법과 본 논문에서 제안된 방식을 MIT/BIH 데이터베이스에서 제공하는 심전도 임상 데이터에 각각 적용하여 비교하였다. 실험을 통해 본 논문에서 제안된 방식이 기존 방식보다 원신호에 대한 데이터 왜곡도가 낮음을 확인하였다.