• Journal of the Korean Data and Information Science Society
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• 제15권1호
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• pp.201-210
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• 2004

The peakedness ordering is closely related to dispersive ordering. In this paper we consider the statistical inference concerning peakedness ordering between two arbitrary symmetric distributions. Nonparametric maximum likelihood estimates of two distribution functions under symmetry and peakedness ordering are given. The likelihood ratio test for equality of two symmetric discrete distributions in the sense of peakedness ordering is studied.

• 한국경영과학회지
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• 제21권3호
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• 한국정보과학회논문지:시스템및이론
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• 제30권10호
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• pp.544-555
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• 2003

DNA 마이크로어레이 실험으로 나오는 데이타는 아주 많은 양의 유전자 발현 정보를 담고 있기 때문에 적절한 분석 방법이 필요하다. 대표적인 분석 방법은 계층적 클러스터링(hierarchical clustering) 방법이다. 본 논문에서는 계층적 클러스터링의 결과로 나오게 되는 덴드로그램(dendrogram)에 대해서 후처리(post-Processing)를 시행함으로써 DNA 마이크로어레이 데이타 분석을 더 용이하게 해주는 리프오더링(leaf-ordering)에 대해서 연구하였다. 먼저, 기존의 리프오더링 알고리즘들을 분석하였고, 리프오더링 알고리즘의 새로운 접근 방식을 제안하였다. 또한 이에 대한 성능을 실험하고 분석하기 위해서 계층적 클러스터링과 몇 가지 리프오더링 알고리즘들, 그리고 제안된 접근 방식을 직접 구현한 HCLO (Hierarchical Clustering & Leaf-Ordering Tool)에 대해서 소개하였다.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.205-216
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• 2019

Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.413-428
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• 2003

If a restriction is imposed only to a (proper) subset of parameters of interest, we call it a local restriction. Statistical inference under a local restriction in multinomial setting is studied. The maximum likelihood estimation under a local restriction and likelihood ratio tests for and against a local restriction are discussed. A real data is analyzed for illustrative purpose.

• 경영과학
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• 제12권2호
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• pp.31-42
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• 1995

The ordering method is used to reduce the fill-ins in interior point methods. In ordering, the data structure plays an important role. In this paper, first, we compare the efficiency and the memory storage requirement of the quotient graph structure and the clique storage. Next, we propose a method of reducing the number of cliques and a data structure for clique storage. Finally, we apply a method of merging rows and absorbing cliques and show the experimental results.

• Industrial Engineering and Management Systems
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• 제11권2호
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• pp.134-141
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• 2012

It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

• International Journal of Advanced Culture Technology
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• 제3권2호
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• pp.1-14
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• 2015

The purpose of this paper is to reveal two problems in the existing inventory systems in retail market, and to suggest a Two-Bin System under Automatic Ordering System considering only base-stock. Large retailers already have a sophisticated inventory system based on an automatic ordering principle. However, why does the out-of-stock (OOS) happen in large discount stores in spite of having a good inventory system? This paper suggests two systems after finding the root causes concerning the previous question. For evaluating the performance of each system, the random 200 data set in each sample group was generated from MINITAB 16 and obeyed the Poisson distribution. The existing inventory system in retail market cannot help generating OOS due to indwelling contradiction in itself. The reasons are the ordering deadline and the relationship between ordering quantity and base stock. This paper also demonstrates that these previous studies on inventory fall into the closed loop. Also the paper shows that the performance of the replenishment policy was better than traditional methods dealing with ordering quantity and base stock.

• 영어어문교육
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• 제15권2호
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• pp.121-150
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• 2009

This paper deals with contrastive analysis and interlanguage with respect to adjective ordering. It aimed to investigate how similar and different the orders of descriptive adjectives are in English and Korean, and how Korean EFL learners perceive the sequences of English descriptive adjectives. Data were collected from native English speakers and native Korean speakers and Korean EFL learners. The contrastive analysis showed that the order of English adjectives was size, opinion, condition, age, color, shape, material, and origin, whereas the Korean order was condition, age, opinion, color, size, shape, material, and origin. The relative order of the interlanguage was shown to be age, size, opinion, shape, condition, color, origin, and material, with the exceptions of the order of condition preceding age and that of size being the same position as condition. The interlanguage data manifested different aspects of ordering when compared with English and Korean: Some adjective combinations were similar to both English and Korean; Some were different from English or Korean; Some were different from both English and Korean. These ordering patterns are discussed in terms of such principles as the nouniness principle, the subjectivity/objectivity principle, the iconic principle, etc. On the basis of these results, some helpful suggestions are made.

• Journal of Smart Tourism
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• 제4권2호
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• pp.25-33
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• 2024

This study examines the factors influencing the use of mobile food ordering applications and their impact on consumption behavior amidst recent societal changes. It re-evaluates the relevance of factors from the UTAUT2 theory in predicting customers' behavioral intentions. Additionally, the study explores the moderating effect of confidence in food safety measures (CFSM). Quantitative research methods are employed. A structured questionnaire that measures the psychological factors, behavioral intention, and actual usage of mobile food ordering applications was used to collect customer data. Regression and moderation analyses are conducted to test the hypotheses and examine the moderating role of CFSM. The findings reveal that performance expectation, effort expectation, and habit significantly predict customers' intention to use mobile food ordering applications. Moreover, for customers with high CFSM, social influence, facilitating conditions, and hedonic motivation add additional contributions to their behavioral intention. This study extends the UTAUT2 theory by applying it to mobile food ordering applications and examining the influence of CFSM. It identifies the specific factors that drive customers' intention to use these applications and highlights the importance of CFSM as a moderating factor. The findings offer theoretical insights and practical implications for researchers and practitioners in the mobile food ordering industry.