• Communications for Statistical Applications and Methods
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• 제2권1호
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• pp.122-136
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• 1995

The objective of this research is to investigate the problem of goodness-of-fit testing based on nonparametric density estimation with a data-driven smoothing parameter. The small and large sample properties of a new test statistic $\hat{\lambda_a}$ is investigated. The test statistic $\hat{\lambda_a}$ is itself a smoothing parameter which is selected to minimize an estimated MISE for a truncated series estimator of the comparison density function. Therefore, this test statistic leads immediately to a point estimate of the density function th the event that $H_0$ is rejected. The limiting distribution of $\hat{\lambda_a}$ is obtained under the null hypothesis. It is also shown that this test is consistent against fixed alternatives.

• 전력전자학회논문지
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• 제12권5호
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• pp.409-415
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• 2007

본 논문에서는 필터 설계시 고려해야 될 주요 항목 중 하나인 성능인자 권장값을 만족시키기 위해 단극 발전기의 내부인자 값을 필터 설계에 반영하는 새로운 평활필터 설계방법을 제안한다. 이 방법은 감쇄용 저항을 배제시킴으로서 평활필터의 효율증대 및 소형화를 기한다. 그리고 성능인자와 함께 공진주파수도 함께 고려함으로서 부성저항 특성을 갖는 고승압 변환기 등을 적용한 시스템의 안정성을 증대시킨다.

• 응용통계연구
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• 제30권5호
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• pp.733-745
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• 2017

국소복합분위수 회귀모형을 활용한 비모수적 함수 추정방법이 높은 효율성과 더불어 활발히 연구되고 있다. 이러한 추정과정에 커널을 사용한 자료 평활방법이 대표적으로 사용되고 있으며, 그 성능은 커널보다는 평활계수의 선택 크게 의존한다. 한편, 회귀함수 추정방법의 성능을 평가하는 기준으로는 통상적으로 $L_2$-노름이 사용되어 평균제곱오차 또는 평균적분제곱오차를 최소화하는 평활계수의 선택에 대한 많은 연구가 진행되어 왔다. 본 논문에서는 국소선형 복합 분위수 회귀방법을 활용한 비모수 회귀모형 추정량의 성능을 결정하는 평활계수 선택의 최적성에 관해 연구하였다. 특히, 여러 장점을 가졌으나 수리적 어려움으로 연구가 미흡한 평균절대오차 및 평균적분절대오차를 최적의 기준으로 삼아 최적의 평활계수를 구하고 그 유일성에 관해 연구하였다. 나아가 기존의 평가기준인 평균제곱오차 및 평균적분제곱오차를 사용한 선택과의 관계를 파악하고 그 성능을 비교하였다. 이러한 과정에서 다양한 상황에서의 모의실험을 통해 제안한 방법의 특성을 규명하였다.

• Industrial Engineering and Management Systems
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• 제7권1호
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• pp.44-50
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• 2008

Focusing on the exponential smoothing method equivalent to (1, 1) order ARMA model equation, a new method of estimating smoothing constant using exponential smoothing method is proposed. This study goes beyond the usual method of arbitrarily selecting a smoothing constant. First, an estimation of the ARMA model parameter was made and then, the smoothing constants. The empirical example shows that the theoretical solution satisfies minimum variance of forecasting error. The new method was also applied to the stock market price of electrical machinery industry (6 major companies in Japan) and forecasting was accomplished. Comparing the results of the two methods, the new method appears to be better than the ARIMA model. The result of the new method is apparently good in 4 company data and is nearly the same in 2 company data. The example provided shows that the new method is much simpler to handle than ARIMA model. Therefore, the proposed method would be better in these general cases. The effectiveness of this method should be examined in various cases.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.215-219
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• 2005

We consider penalized likelihood regression with exponential family responses. Parallel to recent development in Gaussian regression, the fast computation through asymptotically efficient low-dimensional approximations is explored, yielding algorithm that scales much better than the O($n^3$) algorithm for the exact solution. Also customizations of the direct cross-validation strategy for smoothing parameter selection in various distribution families are explored and evaluated.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.809-817
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• 2012

We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.236-241
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• 2022

We consider methods of estimating a binary regression function using a nonparametric kernel estimation when there is only one covariate. For this, the Nadaraya-Watson estimation method using single and double bandwidths are used. For choosing a proper smoothing amount, the cross-validation and plug-in methods are compared. In the real data analysis for case study, German credit data and heart disease data are used. We examine whether the nonparametric estimation for binary regression function is successful with the smoothing parameter using the above two approaches, and the performance is compared.

• Communications for Statistical Applications and Methods
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• 제4권3호
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• pp.911-915
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• 1997

The purpose of this paper is to consider the problem of selection of optimal smoothing parameter for kernel-type distribution function estimator, which asymptotically minimizes mean Hellinger distance.

• 한국자동차공학회논문집
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• 제20권5호
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• pp.152-157
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• 2012

In this paper, smoothing plane connector have been proposed as the vehicle connector for the wireless access in vehicular environments (5.925GHz) communication. This smoothing plane connector is designed by considering the properties of critical parameter like smoothing distance of start to end point of contact area. The design simulation and results can be used to determine the most suitable smoothing plane wire dimensions for vehicle communication connector. The optimized WAVE connector inserted the smoothing plane wire has insertion loss less than-0.17dB at 5.925GHz. It provides 20% of insertion loss with good performance. Therefore, the simulated results can be effectively used for optimum design of high frequency connector for vehicle communication.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1991년도 학술발표회 논문집
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• pp.7-10
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• 1991

In a text-to-speech system, sound units (phonemes, words, or phrases, etc.) can be concatenated together to produce required utterance. The quality of the resulting speech is dependent on factors including the phonological/prosodic contour, the quality of basic concatenation units, and how well the units join together. Thus although the quality of each basic sound unit is high, if occur the discontinuity in the concatenation part then the quality of synthesis speech is decrease. To solve this problem, a smoothing operation should be carried out in concatenation parts. But a major problem is that, as yet, no method of parameter smoothing is available for joining the segment together. Thus in this paper, we proposed a new aigorithm that smoothing the unnatural discountinuous parts which can be occured in speech waveform editing. This algorithm used the exponential smoothing method.