• International Journal of Contents
• /
• 제5권4호
• /
• pp.1-6
• /
• 2009

In this paper, we propose a mesh smoothing method for mesh models with noise. The proposed method enables not only the removal of noise from the vertexes but the preservation and smoothing of shape recognized as edges and comers. The magnitude ratio of 2D area and 3D volume in mesh data is adopted for the smoothing of noise. Comparing with previous smoothing methods, this method does not need many iteration of the smoothing process and could preserve the shape of original model. Experimental results demonstrate improved performance of the proposed approach in 3D mesh smoothing.

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

• Journal of the Korean Data and Information Science Society
• /
• 제18권4호
• /
• pp.945-953
• /
• 2007

In this paper, we propose a smoothing and thus noise-reducing method of data sequences for stock price prediction with hidden Markov models, HMMs. The suggested method just uses simple moving average. A proper average size is obtained from forecasting experiments with stock prices of bank sector of Korean Exchange. Forecasting method with HMM and moving average smoothing is compared with a conventional method.

• Industrial Engineering and Management Systems
• /
• 제8권4호
• /
• pp.257-263
• /
• 2009

Focusing on the idea that the equation of exponential smoothing method (ESM) is equivalent to (1, 1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoothing method is proposed before by us which satisfies minimum variance of forecasting error. Theoretical solution was derived in a simple way. Mere application of ESM does not make good forecasting accuracy for the time series which has non-linear trend and/or trend by month. A new method to cope with this issue is required. In this paper, combining the trend removal method with this method, we aim to improve forecasting accuracy. An approach to this method is executed in the following method. Trend removal by a linear function is applied to the original shipping data of consumer goods. The combination of linear and non-linear function is also introduced in trend removal. For the comparison, monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful especially for the time series that has stable characteristics and has rather strong seasonal trend and also the case that has non-linear trend. The effectiveness of this method should be examined in various cases.

• Asian Journal of Business Environment
• /
• 제11권2호
• /
• pp.27-38
• /
• 2021

Purpose: The study mainly investigates bankruptcy risk and income smoothing tendency of Non-Banking Financial Institutions (NBFIs) in Bangladesh. External parties of NBFIs take investment decisions based on financial reports. Stable and predictable income is one of their preference. On the other hand, poor income is one of the signs of NBFIs having bankruptcy risk. Hence the study tries to find whether the NBFIs having bankruptcy are involved in income smoothing or not. Research design, data and methodology: Data were collected from the annual report of twenty-two listed NBFIs in Bangladesh. Data from 2013 to 2017 were used. Altman's Z score and Eckel's model are used to detecting bankruptcy risk and income smoothing respectively. Results: Result implies that most of the NBFIs which have bankruptcy risk are not involved in income smoothing. Therefore, NBFIs which has bankruptcy risk are involved less with income smoothing. Conclusions: The present study revealed that most of the listed NBFIs in Bangladesh are facing bankruptcy risk. They didn't use any fraudulent technique to show smooth income. The findings will help the investor to take an investment decision on NBFIs in Bangladesh. It will convey signals to the stock market in Bangladesh.

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

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

• Communications for Statistical Applications and Methods
• /
• 제12권3호
• /
• pp.743-758
• /
• 2005

This paper consider penalized likelihood regression with data from exponential family. The fast computation method applied to Gaussian data(Kim and Gu, 2004) is extended to non Gaussian data through asymptotically efficient low dimensional approximations and corresponding algorithm is proposed. Also smoothing parameter selection is explored for various exponential families, which extends the existing cross validation method of Xiang and Wahba evaluated only with Bernoulli data.

• 디지털콘텐츠학회 논문지
• /
• 제13권1호
• /
• pp.111-118
• /
• 2012

버스트는 가변 비트율로 저장된 비디오 데이터를 전송하려는 경우 급격하게 높은 전송률이 요구되는 것으로 네트워크 자원의 비효율적인 사용의 원인이 될 수 있다. 스무딩은 이를 방지하기 위해 가변 비트율로 저장된 비디오 데이터를 고정 비트율로 변환하는 전송 계획을 세우는 기법으로, CBA, MCBA, MVBA 알고리즘들이 있다. 본 논문에서는 기존 CBA, MCBA, MVBA 알고리즘들의 버스트 감소 정도를 평가하기 위해, 가변 비트율로 저장된 비디오 소스와 스무딩 알고리즘에서의 전송 계획을 버스트에 영향을 미치는 요소들로 비교한다. 사용된 평가 요소는 최대 프레임 바이트 수, 최대 GOP 바이트 수, 프레임당 전송률 변화량, GOP당 전송률 변화량이다. 실험 결과, 실험에 사용된 모든 스무딩 알고리즘들의 버스트 관련 평가 요소들이 특정한 경우를 제외하고 원래 비디오 소스보다 낮았다.

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