A two-sample test for high-dimensional normal mean vector

碩士 === 國立清華大學 === 統計學研究所 === 102 === When the data dimension is large relative to the sample size, some of the conventional multivariate testing procedures cannot be applied. Recent studies have proposed some test statistics applicable to high-dimensional data. In this thesis, a new test for testing...

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Main Authors:	Yang, Po-Shun, 楊博舜
Other Authors:	周若珍
Format:	Others
Language:	zh-TW
Published:	2014
Online Access:	http://ndltd.ncl.edu.tw/handle/59332014989853363376

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spelling	ndltd-TW-102NTHU53370262016-03-09T04:31:14Z http://ndltd.ncl.edu.tw/handle/59332014989853363376 A two-sample test for high-dimensional normal mean vector 高維兩常態母體平均向量之檢定 Yang, Po-Shun 楊博舜碩士國立清華大學統計學研究所 102 When the data dimension is large relative to the sample size, some of the conventional multivariate testing procedures cannot be applied. Recent studies have proposed some test statistics applicable to high-dimensional data. In this thesis, a new test for testing the equality of the mean vectors of two independent normal distributed populations is proposed. Furthermore, the asymptotic power function is obtained. Some simulations are carried out to compare its performance with some existing tests under null and alternative hypotheses, respectively. Finally, the test is applied to Plato's works data and DNA microarray gene expression data of colon cancer tissues to see if it can distinguish the difference between two population mean vectors. 周若珍 2014 學位論文 ; thesis 27 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立清華大學 === 統計學研究所 === 102 === When the data dimension is large relative to the sample size, some of the conventional multivariate testing procedures cannot be applied. Recent studies have proposed some test statistics applicable to high-dimensional data. In this thesis, a new test for testing the equality of the mean vectors of two independent normal distributed populations is proposed. Furthermore, the asymptotic power function is obtained. Some simulations are carried out to compare its performance with some existing tests under null and alternative hypotheses, respectively. Finally, the test is applied to Plato's works data and DNA microarray gene expression data of colon cancer tissues to see if it can distinguish the difference between two population mean vectors.
author2	周若珍
author_facet	周若珍 Yang, Po-Shun 楊博舜
author	Yang, Po-Shun 楊博舜
spellingShingle	Yang, Po-Shun 楊博舜 A two-sample test for high-dimensional normal mean vector
author_sort	Yang, Po-Shun
title	A two-sample test for high-dimensional normal mean vector
title_short	A two-sample test for high-dimensional normal mean vector
title_full	A two-sample test for high-dimensional normal mean vector
title_fullStr	A two-sample test for high-dimensional normal mean vector
title_full_unstemmed	A two-sample test for high-dimensional normal mean vector
title_sort	two-sample test for high-dimensional normal mean vector
publishDate	2014
url	http://ndltd.ncl.edu.tw/handle/59332014989853363376
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A two-sample test for high-dimensional normal mean vector

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