Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors
碩士 === 國立中山大學 === 應用數學系研究所 === 92 === In this work, a method to choose the best run order for a given experimental design is proposed, for the simple linear regression model with MA errors. More specifically we investigate the best run order of an uniform design when errors follow a MA(1) or a subse...
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ndltd-TW-092NSYS55070222015-10-13T13:08:02Z http://ndltd.ncl.edu.tw/handle/09368988828178210465 Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors 具有MA誤差之簡單線性迴歸模型下之穩健實驗順序設計 Guo-huai Chiou 邱國輝 碩士 國立中山大學 應用數學系研究所 92 In this work, a method to choose the best run order for a given experimental design is proposed, for the simple linear regression model with MA errors. More specifically we investigate the best run order of an uniform design when errors follow a MA(1) or a subset MA(k) process where k is a positive integer. The correlation matrix P resulting from the errors is usually difficult to obtain a good estimate. Using the change of variance function(CVF) to see the relation of the uncorrelated and the serially correlated errors. Criterion proposed by Zhou (2001), we find the best run order of the uniform design on [-1,1] to minimize the robust criterion, |CVF|. We will display the permutation of a run order after rearrangement by our method and show how the structure is decomposed into three categories to solve the problem. Mong-Na Lo Huang 羅夢娜 2004 學位論文 ; thesis 32 en_US |
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碩士 === 國立中山大學 === 應用數學系研究所 === 92 === In this work, a method to choose the best run order for a given experimental design is proposed, for the simple linear regression model with MA errors. More specifically we investigate the best run order of an uniform design when errors follow a MA(1) or a subset MA(k) process where k is a positive integer. The correlation matrix P resulting from the errors is usually difficult to obtain a good estimate. Using the change of variance function(CVF) to see the relation of the uncorrelated and the
serially correlated errors. Criterion proposed by Zhou (2001), we find the best run order of the uniform design on [-1,1] to minimize the robust criterion, |CVF|. We will display the permutation of a run order after rearrangement by our method and show how the structure is decomposed into three categories to solve the problem.
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author2 |
Mong-Na Lo Huang |
author_facet |
Mong-Na Lo Huang Guo-huai Chiou 邱國輝 |
author |
Guo-huai Chiou 邱國輝 |
spellingShingle |
Guo-huai Chiou 邱國輝 Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors |
author_sort |
Guo-huai Chiou |
title |
Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors |
title_short |
Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors |
title_full |
Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors |
title_fullStr |
Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors |
title_full_unstemmed |
Robust Run Order for Experimental Designs in Simple Linear Regression with MA Errors |
title_sort |
robust run order for experimental designs in simple linear regression with ma errors |
publishDate |
2004 |
url |
http://ndltd.ncl.edu.tw/handle/09368988828178210465 |
work_keys_str_mv |
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