A Study of Finding Optimum Variance Function in Generalized Mixed Models

碩士 === 國立臺灣大學 === 農藝學研究所 === 90 === Because GLIM can be applied non-normal data in different situations in recent years, GLIMM with random factors make the applied area more widely. If the users decided the distribution in the program when they analyze by statistical software SAS MACRO GL...

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Main Authors: LI-TUNG-CHIANG, 李永卿
Other Authors: YUN-MING-PONG
Format: Others
Language:zh-TW
Published: 2002
Online Access:http://ndltd.ncl.edu.tw/handle/21062032621233310898
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spelling ndltd-TW-090NTU004170212015-10-13T14:38:19Z http://ndltd.ncl.edu.tw/handle/21062032621233310898 A Study of Finding Optimum Variance Function in Generalized Mixed Models 廣義線型混和模式最適變方函數選擇之研究 LI-TUNG-CHIANG 李永卿 碩士 國立臺灣大學 農藝學研究所 90 Because GLIM can be applied non-normal data in different situations in recent years, GLIMM with random factors make the applied area more widely. If the users decided the distribution in the program when they analyze by statistical software SAS MACRO GLIMMIX, variance function would be decided. But in residual plots, maybe we can't have reasonable explanation. So it is the purpose of this paper to choose the variance function properly. In the study, we offer three methods to choose the optimal variation function, and use one data group of the Phototaxis of Alates of Coptotermes formosanus Shiraki to explain the three methods. We find that it would have better explanation for data. Because residuals are better scattered and have no obvious pattern. So when the data for analyzing is mixed, we suggest that finding the optimal variation function first then analyze GLIMMIX. YUN-MING-PONG 彭雲明 2002 學位論文 ; thesis 40 zh-TW
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description 碩士 === 國立臺灣大學 === 農藝學研究所 === 90 === Because GLIM can be applied non-normal data in different situations in recent years, GLIMM with random factors make the applied area more widely. If the users decided the distribution in the program when they analyze by statistical software SAS MACRO GLIMMIX, variance function would be decided. But in residual plots, maybe we can't have reasonable explanation. So it is the purpose of this paper to choose the variance function properly. In the study, we offer three methods to choose the optimal variation function, and use one data group of the Phototaxis of Alates of Coptotermes formosanus Shiraki to explain the three methods. We find that it would have better explanation for data. Because residuals are better scattered and have no obvious pattern. So when the data for analyzing is mixed, we suggest that finding the optimal variation function first then analyze GLIMMIX.
author2 YUN-MING-PONG
author_facet YUN-MING-PONG
LI-TUNG-CHIANG
李永卿
author LI-TUNG-CHIANG
李永卿
spellingShingle LI-TUNG-CHIANG
李永卿
A Study of Finding Optimum Variance Function in Generalized Mixed Models
author_sort LI-TUNG-CHIANG
title A Study of Finding Optimum Variance Function in Generalized Mixed Models
title_short A Study of Finding Optimum Variance Function in Generalized Mixed Models
title_full A Study of Finding Optimum Variance Function in Generalized Mixed Models
title_fullStr A Study of Finding Optimum Variance Function in Generalized Mixed Models
title_full_unstemmed A Study of Finding Optimum Variance Function in Generalized Mixed Models
title_sort study of finding optimum variance function in generalized mixed models
publishDate 2002
url http://ndltd.ncl.edu.tw/handle/21062032621233310898
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