• 한국의류학회지
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• 제11권3호
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• pp.111-119
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• 1987

The main purposes of the study were to categorize the clothing items into product groups according to their product characteristics, and to find out the differences of consumer perception on clothing Product groups among different age and socioeconomic groups. A questionnaire about characteristics It?as constructed on the basis of Lipton, Darling, and Miracle's theories on product categorisations. The questionnaires were administered to female subjects in two age groups (20's and 40's) living in Seoul. Subjects were classified into 3 socioeconomic groups for the analysis. The Analysis of variance, post-hoc comparisons (Scheffe test and Tuckey test) were employed for the statistical inferences. The results were as follows ; Group I : none Group II : socks, undershirts, T-shirts (20's age group) Group III : blouse, sweater, blue jean, pajama, langerie, T-shirts (40's age group), skirt Group IV : jacket, skirt (high class of 40's age group) two-piece, half coat, long coat, Korean folk costume Group V : none Some of the clothing items were categorized into different product groups by different age and socioeconomic groups.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1201-1208
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• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• 응용통계연구
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• 제21권5호
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• pp.835-843
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• 2008

In this paper, we investigate a Bayesian inference for software reliability models based on mean value functions which take the form of the mixture of beta distribution functions. The posterior simulation via the Markov chain Monte Carlo approach is used to produce estimates of posterior properties. Its applicability is illustrated with two real data sets. We compute the predictive distribution and the marginal likelihood of various models to compare the performance of them. The model comparison results show that the model based on the beta-mixture performs better than other models.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2010년도 춘계학술대회
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• pp.33-48
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• 2010

The purpose of this study is to empirically analyze the productivity change of the 10 Single PPM Certification Company in the 3 Industry(Electronics, Motor-Parts, Machines). In this study, Productivity change over the time in Korean small and medium sized firms in the 3 industries by the bootstrapped Malmquist Productivity Index(MPI). The traditional Malmquist Productivity Index(MPI) and Data Envelopment they could lead to wrong evaluations of the efficiency and productivity scores. In this paper, DEA and a MPI are combined with a bootstrap method in order to provide statistical inferences that analyze the performance of the Single PPM Certification Company. The data cover the period between 2004 and 2007. The result of this paper reveals : 1) The electronic industries(Motor-Parts, Machines). 2) average productivity Progress of the 7DMU(Electronics), 1DMU(Motor-Parts) and none(Machines).

• Asian-Australasian Journal of Animal Sciences
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• 제11권6호
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• pp.642-647
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• 1998

A Poisson error model as a generalized linear mixed model (GLMM) has been suggested for genetic analysis of counted observations. One of the assumptions in this model is the normality for random effects. Since this assumption is not always appropriate, a more flexible model is needed. For count traits, a Poisson hierarchical generalized linear model (HGLM) that does not require the normality for random effects was proposed. In this paper, a Poisson-Gamma HGLM was examined along with corresponding analytical methods. While a difficulty arises with Poisson GLMM in making inferences to the expected values of observations, it can be avoided with the Poisson-Gamma HGLM. A numerical example with simulated embryo yield data is presented.

• 응용통계연구
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• 제18권1호
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• pp.173-182
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• 2005

순서를 갖는 범주형자료의 분석을 위한 중요한 통계적 방법인 순위로짓모형의 대안으로 무정보 사전분포에 의한 베이지안 분계점 모형을 정의하고, 실증 자료분석을 통해 베이지안 모형의 유용성을 살펴보았다.

• 응용통계연구
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• 제25권4호
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• pp.641-650
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• 2012

Spatial time series data can be viewed as a set of time series simultaneously collected at a number of spatial locations. This paper studies Bayesian inferences in a spatial time bilinear model with a Gibbs sampling algorithm to overcome problems in the numerical analysis techniques of a spatial time series model. For illustration, the data set of mumps cases reported from the Korea Center for Disease Control and Prevention monthly over the years 2001~2009 are selected for analysis.

• 응용통계연구
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• 제9권1호
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• pp.165-177
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• 1996

제한된 t 분포로부터의 난수 생성은 특히 베이지안 분석에서 제한이 있는 모수의 사후밀도함수를 추정하기 위하여 몬테카를로 적분을 하는 경우 등에 필요하다. 그런데 제한영역이 t분포의 극단 꼬리부분으로 주어졌을 때 기존의 난수생성기법의 적용은 매우 비효율적이 될 수 있다. 본 논문에서는 난수생성 알고리즘을 제시하과 기존의 기법들과 시뮬레이션을 통하여 효율을 비교하였다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 추계 학술발표회 논문집
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• pp.21-27
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• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• 응용통계연구
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• 제6권2호
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• pp.435-442
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• 1993

일반화 감마분포 모형에서 지표모수(k)가 알려진 경우에는 백분위 수에 대한 정확한 추론이 가능하다. 이 방법은 정확한 결과를 제공하지만 복잡한식의 수치적 계산이 요구된다. 본 논문에서는 이러한 계산상의 어려움을 극복함과 동시에 거의 대등한 정확도를 유지하는 근사신뢰구간을 구하였다. 또한, 로그정규모형에 대해서도 그 결과를 적용시켜 보았다.