首页> 外文学位 >The analysis of location and dispersion effects in unreplicated 2(k) factorial experiments.
【24h】

The analysis of location and dispersion effects in unreplicated 2(k) factorial experiments.

机译:在未复制的2(k)阶乘实验中对位置和分散效应的分析。

获取原文
获取原文并翻译 | 示例

摘要

If an experiment takes place in the early stages of a research process, the purpose is often to quickly and efficiently screen or identify factors or interactions that significantly impact a response variable. These types of experiments are referred to as screening experiments. Factorial and fractional factorial experiments are commonly used as screening experiments because they allow for the simultaneous investigation of a large number of factors with relatively few experimental runs. If the resources available for the experiment are limited, the experiment may not contain replicates.; Screening experiments have historically been used to identify location effects or effects that influence the mean of a response variable. Hamada and Balakrishnan (1998) give an extensive overview of many existing methods for the identification of location effects. Loughin and Noble (1997) propose a permutation-based approach for the identification of active effects that appears to perform better than most existing methods when there are a large number of active effects relative the number of experimental runs. The large sample properties of their test procedure is investigated. In addition, four large sample approximations are presented and empirically compared to Loughin and Noble's permutation procedure.; More recently, due in part to the incorporation of Taguchi-type philosophies into experimentation, screening experiments have been used to identify dispersion effects, or effects that influence the variance of a response variable. Brenneman and Nair (2001) give an overview of existing dispersion testing methods. In addition, McGrath and Lin (2001) find that two unidentified location effects may cause a spurious dispersion effect and state that additional replication is necessary to identify the true cause of the disturbance in the response variable. A procedure is developed under an additive variance model which allows for the separation of location effects from dispersion effects without the need for additional experimentation. More importantly, it is shown that masking of an active dispersion effect may occur and unlike existing methods, the proposed procedure is robust to this phenomenon. A simulation study is used to compare the proposed procedure with commonly cited procedures.
机译:如果实验是在研究过程的早期进行的,则通常目的是快速有效地筛选或识别对响应变量有重大影响的因素或相互作用。这些类型的实验称为筛选实验。阶乘和分数阶乘实验通常用作筛选实验,因为它们允许在相对较少的实验运行中同时研究大量因子。如果可用于实验的资源有限,则该实验可能不包含重复项。筛选实验在历史上一直用于识别位置效应或影响响应变量平均值的效应。 Hamada和Balakrishnan(1998)对确定位置效应的许多现有方法进行了广泛的概述。 Loughin and Noble(1997)提出了一种基于排列的方法来识别主动效应,当相对于实验运行次数有大量主动效应时,该方法似乎比大多数现有方法表现更好。他们的测试程序的大样本属性进行了调查。另外,提出了四个大样本近似值,并与Loughin和Noble的置换程序进行了经验比较。最近,部分由于田口类型哲学被纳入实验,筛选实验已被用于识别分散效应或影响响应变量方差的效应。 Brenneman和Nair(2001)概述了现有的色散测试方法。此外,McGrath和Lin(2001)发现,两个不确定的位置效应可能会导致杂散效应,并指出需要额外的复制才能确定响应变量中干扰的真正原因。在加性方差模型下开发了一种程序,该程序允许将位置效应与分散效应分离,而无需进行其他实验。更重要的是,表明可能会掩盖主动色散效应,并且与现有方法不同,所提出的过程对这种现象具有鲁棒性。仿真研究用于将建议的过程与通常引用的过程进行比较。

著录项

  • 作者

    Malone, Christopher John.;

  • 作者单位

    Kansas State University.;

  • 授予单位 Kansas State University.;
  • 学科 Statistics.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 197 p.
  • 总页数 197
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 统计学;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号