• 제목/요약/키워드: one way layout

검색결과 76건 처리시간 0.018초

Nonparametric Method Using Placement in One-way Layout

  • Chung, Taek-Su;Kim, Dong-Jae
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.551-560
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    • 2007
  • Kruskal and Wallis (1952) proposed typical nonparametric method in one-way layout problem. A special feature of this procedure is use of rank in mixed samples. In this paper, the new procedure based on placement as extension of the two sample placement tests described in Orban and Wolfe (1982) was proposed. Some critical values in small sample cases and comparative results of a Monte Carlo power study are presented.

다중 베이 제조시스템의 설비배치 (Layout Design Problem in Multi-bay Facility)

  • 이문수;채준재
    • 산업경영시스템학회지
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    • 제32권4호
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    • pp.93-100
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    • 2009
  • This paper addresses the facility layout problem in multi-bay environments, where the bays are connected at one or both ends by an inter-bay material handling system. In most previous studies, the main concern is to allocate facilities or departments to the bays whose widths are fixed. In this research, we suggest the efficient models that provide the optimal layout solution under flexible bay width environments. We also suggest a mathematical model that provides the optimal solution using two-way facility allocation approach instead of one-way allocation technique. This paper also shows the approach of TABU search to the assignment and layout design of the departments. The results generated from TABU search are compared to the result from the mathematical model. Models are developed using mixed integer programming for various test problems and solved by CPLEX.

일원배치법에서 결합위치를 이용한 비모수 검정법 (Nonparametric method in one-way layout based on joint placement)

  • 전경아;김동재
    • 응용통계연구
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    • 제29권4호
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    • pp.729-739
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    • 2016
  • 독립된 세 개 이상의 처리 간에 차이 유무를 검정하는 비모수적 방법에는 Kruskal과 Wallis (1952)가 제안한 검정법이 있다. 세 개 이상의 다른 모집단으로부터 결합된 표본관측 값들의 순위를 이용한 검정기법이다. 본 논문에서는 Chung과 Kim (2007)이 제안한 결합위치 방법을 확장하여 일원배치모형에서 새로운 방법을 제안하였다. 또한 모의실험(Monte Calro simulation study)를 통하여 기존의 검정법과 제안한 방법의 검정력을 비교하였다.

Multiple Comparisons With the Best in the Analysis of Covariance

  • Lee, Young-Hoon
    • Journal of the Korean Statistical Society
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    • 제23권1호
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    • pp.53-62
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    • 1994
  • When a comparison is made with respect to the unknown best treatment, Hsu (1984, 1985) proposed the so called multiple comparisons procedures with the best in the analysis of variance model. Applying Hsu's results to the analysis of covariance model, simultaneous confidence intervals for multiple comparisons with the best in a balanced one-way layout with a random covariate are developed and are applied to a real data example.

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Detection of Random Effects in a Random Effects Model of a One-way Layout Contingency Table

  • Kim, Byung-Soo
    • Journal of the Korean Statistical Society
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    • 제13권1호
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    • pp.1-19
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    • 1984
  • A random effects model of a one-way layout contingency table is developed using a Dirichlet-multinomial distribution. A test statistic, say $T_k$, is suggested for detecting Dirichlet-multinomial departure from a multinomial distribution. It is shown that the $T_k$ test is asymptotically superior to the classical chi-square test based on the asymptotic relative efficiency. This superiority is further evidenced by a Monte Carlo simulation.

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A Modified Chen-Wolfe Procedure for Comparing Umbrella Pattern Treatment Effects with a Control in a One-way Layout

  • Lim, Dong-Hoon;Kim, Soo-Taek;Park, Joong-Yang
    • Communications for Statistical Applications and Methods
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    • 제3권1호
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    • pp.145-153
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    • 1996
  • Nonparametric tests for comparing umbrella pattern treatment effects with a control in a one-way layout were studied in Chen and Wolfe (1993). In this paper we propose a modification that improves the power of the Chen-Wolfe test. The results of a Monte Carlo power study are discussed.

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일원배치모형에서 결합위치를 이용한 비모수 다중비교법 (Nonparametric multiple comparison method in one-way layout based on joint placement)

  • 석다희;김동재
    • 응용통계연구
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    • 제30권6호
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    • pp.1027-1036
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    • 2017
  • 일원배치모형에서 세 개 이상의 처리 간에 차이 유무를 검정하여 귀무가설이 기각됐다면, 어떤 것이 통계적으로 유의한 결과인지 확인하기 위해서는 다중비교 방법이 필요하다. 대표적인 모수적 검정법으로는 Tukey (1953), 비모수적 검정법으로는 Kruskal-Wallis (1952)의 검정에 기초한 방법이 있다. 이 방법은 전체 자료에 대한 혼합표본에 순위를 부여한 후 세 개 이상의 각 처리별 평균 순위를 이용한 검정방법이다. 본 논문에서는 Chung과 Kim (2007)이 제안한 결합위치 검정법을 확장하여 일원배치모형에서 새로운 비모수적 다중비교 방법을 제안하였다. 또한 모의실험(Monte Carlo simulation)을 통해 기존의 검정방법들과 제안한 방법의 family wise error rate (FWE)와 검정력을 비교하였다.

회전을 고려한 판재 배치 문제의 유전 알고리즘 적용 (Application of the Genetic Algorithm to the Layout Problem of the Pane Considering Rotation)

  • 이금탁;김훈모
    • 제어로봇시스템학회논문지
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    • 제6권5호
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    • pp.376-382
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    • 2000
  • A problem of relevant interest to some industries is that of the optimum two-dimensional layout. In this problem, one is given a number of rectangular sheets and an order for a specified number of each of certain types of two-dimensional regular and irregular shapes. The aim is to cut the shapes out of the sheets in such a way as to minimize the amount of waste produced. In this paper, we propose a genetic algorithms using rotation parameters by which the best pattern of layout is found.

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일원배치법에서 Umbrella Alternatives에 대한 위치를 이용한 비모수 검정법 (Nonparametric Method in One-way Layout for Umbrella Alternatives based on Placement)

  • 이혜정;김동재
    • 응용통계연구
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    • 제28권6호
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    • pp.1181-1189
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    • 2015
  • 임상시험에서 약의 복용량에 따라 처리 효과가 증가하다가, 부작용으로 인해 일정 용량 수준에서 감소하는 추세를 보일 수 있다. 이러한 경향을 우산형 패턴이라 하며, 우산형 패턴의 대립가설에 대한 검정은 이러한 경향이 사전에 예측 가능할 때 유용하다. 이 논문에서는 Orban과 Wolfe (1982)가 제안한 선형 위치(linear placement)를 이용하여 일원배치법에서 우산형 대립가설의 비모수적 검정법을 제안하였다. 또한 Monte Carlo 모의실험을 통하여 기존의 방법들과 검정력(power)을 비교하였다.

A study On An Identification of Interactions In A Nonreplicated Two-Way Layout With $L_1$-Estimation

  • Lee, Ki-Hoon
    • Communications for Statistical Applications and Methods
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    • 제7권1호
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    • pp.119-128
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    • 2000
  • This paper proposes a method for detecting interactions in a two-way layout with one observation per cell. The identification of interactions in the model is not clear for they are confounding with error terms. The $L_1$-Estimation is robust with respect to a y-direction outlier in linear model so we are able to estimate main effects without affection of interactions, If an observation is classified as an outlier we conclude it contains an interaction. An empirical study compared with a classical method is performed.

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