Estimations for some functions of covariance matrix in high dimension under non-normality and its applications
書誌事項
- 公開日
- 2014-09
- 資源種別
- journal article
- 権利情報
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- https://www.elsevier.com/tdm/userlicense/1.0/
- https://www.elsevier.com/open-access/userlicense/1.0/
- DOI
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- 10.1016/j.jmva.2014.04.020
- 公開者
- Elsevier BV
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説明
When we consider a statistical test in the high dimensional case, we often need estimators of the functions of the covariance matrix @S. Especially, it is needed to estimate a"2=(1/p)[email protected]^2. The unbiased and consistent estimator of a"2 is proposed in preceding study when the population distribution is multivariate normal. But it is difficult to estimate in the non-normal case. So we propose the unbiased and consistent estimators for some functions of covariance matrix including a"2 under the non-normal case. Through the numerical simulation, we confirmed the accuracy of the approximation of our proposed estimators. Using proposed estimators, we proposed a test for assessing multivariate normality of the high-dimensional data.
収録刊行物
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- Journal of Multivariate Analysis
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Journal of Multivariate Analysis 130 27-44, 2014-09
Elsevier BV
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詳細情報 詳細情報について
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- CRID
- 1360285707273669376
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- ISSN
- 0047259X
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- 資料種別
- journal article
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- データソース種別
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- KAKEN
- OpenAIRE