• 제목/요약/키워드: Statistical design

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효율적인 감성공학적 인테리어 디자인 분석 도구의 설계 (Design of an Effective Human Sensibility Ergonomic Interior Design Analysis Tool)

  • 서형수
    • 한국실내디자인학회논문집
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    • 제16권2호
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    • pp.314-321
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    • 2007
  • The statistical method of human sensibility ergonomics is widely used for analyzing interior design because it has standard processes and it can help to get quantifiable results. However applying this method demands repeated intense work and great time and effort is required. In this study, a tool applying Web and virtual reality techniques for statistical human sensibility ergonomic interior design analysis is proposed and the key parts of the tool including database and interface are implemented. The database contains the sensibility adjective table and the physical interior design factor table for analyzing the relationship between human sense and physical design factors. Interface of the tool is implemented using Web technologies, so testers can evaluate interior design samples via standard Web browsers. The 3D control which is an important component of the interface is also implemented. Employing the suggested tool can reduce effort and time for evaluating human sense in Interior design field.

통계적 공정관리를 위한 주요 통계패키지의 비교 (Comparison of statistical packages useful for statistical process control)

  • 조신섭;신봉섭
    • 응용통계연구
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    • 제10권1호
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    • pp.29-36
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    • 1997
  • 본 비교연구는 국내에 소개되어 있는 통계패키지 중에서 기업의 품질경영(관리)이나 업무분석 등 공정관리와 연관된 패키지의 특성이나 기능등을 비교하였다. 일반적으로 많이 사용되고 있는 윈도우즈 버젼의 MINITAB, RS, SAS, SPSS가 고려되었다. 각 패키지의 일반적 특성과 가격 등을 알아보고 관리도 및 공정능력분석, 실험계획법과 다구찌 방법 등의 공정관리와 연관된 프로시져들을 중심으로 비교하였으며, 패키지를 선택할 때 고려하여야 할 기본적인 사항에 대하여도 언급하였다.

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R: AN OVERVIEW AND SOME CURRENT DIRECTIONS

  • Tierney, Luke
    • Journal of the Korean Statistical Society
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    • 제36권1호
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    • pp.31-55
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    • 2007
  • R is an open source language for statistical computing and graphics based on the ACM software award-winning S language. R is widely used for data analysis and has become a major vehicle for making available new statistical methodology. This paper presents an overview of the design philosophy and the development model for R, reviews the basic capabilities of the system, and outlines some current projects that will influence future developments of R.

Hybrid Approach When Multiple Objectives Exist

  • Kim, Young-Il;Lim, Yong-Bin
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.531-540
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    • 2007
  • When multiple objectives exist, there are three approaches exist. These are maximin design, compound design, and constrained design. Still, each of three design criteria has its own strength and weakness. In this paper Hybrid approach is suggested when multiple design objectives exist, which is a combination of maximin and constrained design. Sometimes experimenter has several objectives, but he/she has only one or two primary objectives, others less important. A new approach should be useful under this condition. The genetic algorithm is used for few examples. It has been proven to be a very useful technique for this complex situation. Conclusion follows.

Model-Based Prediction of the Population Proportion and Distribution Function Using a Logistic Regression

  • Park, Min-Gue
    • Communications for Statistical Applications and Methods
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    • 제15권5호
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    • pp.783-791
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    • 2008
  • Estimation procedure of the finite population proportion and distribution function is considered. Based on a logistic regression model, an approximately model- optimal estimator is defined and conditions for the estimator to be design-consistent are given. Simulation study shows that the model-optimal design-consistent estimator defined under a logistic regression model performs well in estimating the finite population distribution function.

Nonparametric Procedures for Comparing Ordered Treatment Effects with a Control in a Randomized Block Design

  • Lim, Dong-Hoon
    • Journal of the Korean Statistical Society
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    • 제26권1호
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    • pp.89-100
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    • 1997
  • In this paper we are concerned with comparing ordered treatment effects with a control in a randomized block design with multiple observations per cell. Two nonparametric procedures for detecting which treatment are better than the control are proposed and compared. An example is given and the results of a Monte Carlo power study are discussed.

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An Orthogonal Representation of Estimable Functions

  • Yi, Seong-Baek
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.837-842
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    • 2008
  • Students taking linear model courses have difficulty in determining which parametric functions are estimable when the design matrix of a linear model is rank deficient. In this note a special form of estimable functions is presented with a linear combination of some orthogonal estimable functions. Here, the orthogonality means the least squares estimators of the estimable functions are uncorrelated and have the same variance. The number of the orthogonal estimable functions composing the special form is equal to the rank of the design matrix. The orthogonal estimable functions can be easily obtained through the singular value decomposition of the design matrix.

Construction of Second Order Slope Rotatable Designs Using Symmetrical Unequal Block Arrangements with Two Unequal Block Sizes

  • Babu, B.Re.Victor
    • Journal of the Korean Statistical Society
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    • 제31권2호
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    • pp.153-161
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    • 2002
  • A new method of construction of second order slope rotatable designs (SOSRD) using symmetrical unequal block arrangements (SUBA) with two unequal block sizes is suggested. The proposed method may sometimes lead to designs with less number of design points than those available in the literature. Further, bounds for the parameters of SOSRD are also obtained.

Rank transform F statistic in a 2$\times$2 factorial design

  • Park, Young-Hun
    • Journal of the Korean Statistical Society
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    • 제23권1호
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    • pp.103-114
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    • 1994
  • For a $2 \times 2$ factorial design without the restriction of a linear model or without regard to error terms having homoscedasticity, under the null hypothesis of no interaction we can have the rank transformed F statistic for interaction converge in distribution to a chi-squared random variable with one degree of random if and only if there is only main effect.

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Heteroscedasticity of Random Effects in Crossover Design

  • 안철환
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2002년도 추계 학술발표회 논문집
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    • pp.79-83
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    • 2002
  • A phase III clinical trial of a new drug for neutropenia induced by chemotherapy is presented and consider adding random effects in crossover design which was used in the clinical study. The diagnostics for its heteroscedasticity based on score statistic is derived for detecting homoscedasticity of errors in crossover design. A small simulation study is peformed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.

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