Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample

碩士 === 靜宜大學 === 應用數學研究所 === 92 === For a random effect model in the experimental design, an exact confidence interval on a variance component usually cannot be obtained, so an approximation has to be used. One of the useful procedures is the modified large-sample(MLS) method. The confidence coeffi...

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Main Authors: Pin-Yen Chou, 周品妍
Other Authors: mone
Format: Others
Language:zh-TW
Published: 2004
Online Access:http://ndltd.ncl.edu.tw/handle/pqj7n7
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spelling ndltd-TW-092PU0055070112019-05-15T19:19:26Z http://ndltd.ncl.edu.tw/handle/pqj7n7 Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample 小樣本變異分量非負線性組合之區間估計 Pin-Yen Chou 周品妍 碩士 靜宜大學 應用數學研究所 92 For a random effect model in the experimental design, an exact confidence interval on a variance component usually cannot be obtained, so an approximation has to be used. One of the useful procedures is the modified large-sample(MLS) method. The confidence coefficients of this method are not good enough when the sample size is small or a one-tailed problem is considered. Therefore, for the case of small samples, two new methods were proposed to get a confidence lower limit for a nonnegative linear combination of two variance components, . These methods are trial-and-error method and functional method. The lower confidence limit given by either method had a special form as , where and are the unbiased minimum variance estimators of and respectively, and . The g-function for the trial-and-error method was obtained by manually adjusting the error, resulting in an error within 0.05%. The g-function for the functional method was obtained by using a numerical technique which minimize the sum of the square errors, resulting in an error within 1.78%. The value of the desired g-function can be easily obtained according to the graphics or the tables presented in this thesis, then the lower confidence limit for will be found. mone 陳臺芳 2004 學位論文 ; thesis 46 zh-TW
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language zh-TW
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description 碩士 === 靜宜大學 === 應用數學研究所 === 92 === For a random effect model in the experimental design, an exact confidence interval on a variance component usually cannot be obtained, so an approximation has to be used. One of the useful procedures is the modified large-sample(MLS) method. The confidence coefficients of this method are not good enough when the sample size is small or a one-tailed problem is considered. Therefore, for the case of small samples, two new methods were proposed to get a confidence lower limit for a nonnegative linear combination of two variance components, . These methods are trial-and-error method and functional method. The lower confidence limit given by either method had a special form as , where and are the unbiased minimum variance estimators of and respectively, and . The g-function for the trial-and-error method was obtained by manually adjusting the error, resulting in an error within 0.05%. The g-function for the functional method was obtained by using a numerical technique which minimize the sum of the square errors, resulting in an error within 1.78%. The value of the desired g-function can be easily obtained according to the graphics or the tables presented in this thesis, then the lower confidence limit for will be found.
author2 mone
author_facet mone
Pin-Yen Chou
周品妍
author Pin-Yen Chou
周品妍
spellingShingle Pin-Yen Chou
周品妍
Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample
author_sort Pin-Yen Chou
title Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample
title_short Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample
title_full Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample
title_fullStr Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample
title_full_unstemmed Interval Estimation on the Non-negative Linear Combination of Variance Components for Small Sample
title_sort interval estimation on the non-negative linear combination of variance components for small sample
publishDate 2004
url http://ndltd.ncl.edu.tw/handle/pqj7n7
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