• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1093-1102
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• 2012

본 연구에서는 다변량시계열모형인 VAR (vector autoregressive regression)모형에 의하여 금리 스프레드의 시계열예측을 수행하였다. 국내외 거시경제변수들 중에서 교차상관분석 및 그랜져인과 검정을 통하여 상호간에 설명력이 있는 변수들을 추출하여 VAR모형의 시계열변수로 사용하였다. 마지막 12개월의 예측치에 대한 MAPE (mean absolute percentage error)와 RMSE (root mean square error)에 근거하여 모형의 예측력을 단일변량 시계열모형인 AR (autoregressive regression) 모형과 비교하였다.

• 한국신뢰성학회지:신뢰성응용연구
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• 제11권2호
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• pp.177-186
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• 2011

Traditionally, one uses a method of straight-line recognition to evaluate quality of product or service. One can satisfy with the product or service if their physical requirement of are met some criterions and can not satisfy them if their physical requirement are not met. Kano, et al(1984) introduce two dimensional Quality model to evaluate quality of product or service. They classify Quality Characteristic of product and service to three categories; satisfying quality, attractive quality, expected quality. In this paper, 17 evaluation features in 6 categories of smart-card are obtained from Focus-interview and Brainstorming and classified into 3 categories of quality model by Kano's two dimensional method. This classification is expected to provide a guideline for evaluation of smart-card.

• 응용통계연구
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• 제23권5호
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• pp.933-941
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• 2010

행렬도는 고차원의 자료를 저차원 공간에 투영하여 자료를 시각화하는 비교적 현대적인 방법으로써, 자료의 산포도, 집단 구분, 변수사이의 상관관계 등 유용한 정보들을 제공한다. 본 연구에서는 이러한 행렬도를 간략하게 소개하고, 행렬도의 구현을 위해 대중성이 높아지고 있는 무료 소프트웨어인 R의 BiplotGUI 패키지를 사용하였다. 그리고 전북대학교에서 2009년도에 실시된 신입생의 진로의식 조사 자료를 이용하여, 신입생의 선호직업과 진로성숙도의 관계를 행렬도 분석방법으로 살펴보았다.

• Journal of the Korean Statistical Society
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• 제11권2호
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• pp.109-117
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• 1982

In this paper, a preliminary study is performed on the subset selection procedures which are based on the trimmed means and the Hodges-Lehmann estimator derived from the Wilcoxon test. The proposed procedures are compared to the Gupta's rule through a small smaple Monte Carlo study. The results show that the procedures based on the robust estimators are successful in terms of efficiency and robustness.

• International Journal of Reliability and Applications
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• 제1권2호
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• pp.155-165
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• 2000

In this paper, we propose some estimators of Kullback- Leibler Information functions using the data from three step stress accelerated life tests. This acceleration model is assumed to be a tampered random variable model. Some asymptotic properties of proposed estimators are proved. Simulations are performed for comparing the small sample properties of the proposed estimators under use condition of accelerated life test.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.571-579
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• 1998

In this paper we propose smooth nonparametric estimator of Mean Residual Life(MRL) based on a complete sample. This estimator is constructed using estimator of cumulative failure rate which is derived as the maximum likelihood estimate of cumulative failure rate in the class of distributions which have piecewise linear failure rate functions between each pair of observations. We derive the asymptotic properties of the our estimator. The proposed estimator is compared with previously known estimator by Monte Carlo study.

• Journal of the Korean Data and Information Science Society
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• 제4권
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• pp.87-95
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• 1993

We find a class of admissible Bayes estimator for the mean vector ${\theta}=({\theta}_{1},{\theta}_{2},...,{\theta}_{p}$ of Poisson distribution under a LINEX loss function. The Monte Carlo Simulation is performed to compare the emprical Bayes estimater under the LINEX loss function and weighted squared error loss respectively.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.111-119
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• 2007

In this paper, we develop a nonparametric Bayesian methodology of estimating an unknown distribution function F at the given survival time with current status data under the assumption of Dirichlet process prior on F. We compare our algorithm with the nonparametric maximum likelihood estimator through application to simulated data and real data.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.11-21
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• 2007

In this paper, we consider a decision-theoretic oriented, objective Bayesian inference for the difference between two normal means with unknown com-mon variance. We derive the Bayesian reference criterion as well as the intrinsic estimator and the credible region which correspond to the intrinsic discrepancy loss and the reference prior. We illustrate our results using real data analysis as well as simulation study.

• 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.