Testing multinormality based on low-dimensional projection
文献类型：期刊论文
| 作者 | Liang, JJ; Li, RZ; Fang, HB; Fang, KT |
| 刊名 | JOURNAL OF STATISTICAL PLANNING AND INFERENCE
 |
| 出版日期 | 2000-04-15 |
| 卷号 | 86期号:1页码:129-141 |
| 关键词 | left-spherical matrix distributions Mardia's skewness and kurtosis projection tests testing multinormality |
| ISSN号 | 0378-3758 |
| 英文摘要 | A method based on properties of left-spherical matrix distributions and affine invariant statistics is employed to construct projection tests for multivariate normality. The projection tests are indirectly dependent on the dimension of raw data. As a result, the projection tests can be performed for arbitrary dimension d and sample size n even if n < d in high-dimensional case as soon as the projection dimension is suitably chosen. By Monte Carlo simulation, we show that the projection tests significantly improve the power of existing tests for multinormality in the case of high dimension with a small sample size. Analysis on a practical example shows that the projection tests are useful complements to existing tests for multinormality. (C) 2000 Elsevier Science B.V. All rights reserved. |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000085999800009 |
| 出版者 | ELSEVIER SCIENCE BV |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/14963]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 作者单位 | 1.Hong Kong Baptist Univ, Dept Math, Hong Kong, Hong Kong, Peoples R China 2.Chinese Acad Sci, Inst Appl Math, Beijing, Peoples R China 3.Univ N Carolina, Dept Stat, Chapel Hill, NC 27599 USA |
| 推荐引用方式 GB/T 7714 | Liang, JJ,Li, RZ,Fang, HB,et al. Testing multinormality based on low-dimensional projection[J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE,2000,86(1):129-141. |
| APA | Liang, JJ,Li, RZ,Fang, HB,&Fang, KT.(2000).Testing multinormality based on low-dimensional projection.JOURNAL OF STATISTICAL PLANNING AND INFERENCE,86(1),129-141. |
| MLA | Liang, JJ,et al."Testing multinormality based on low-dimensional projection".JOURNAL OF STATISTICAL PLANNING AND INFERENCE 86.1(2000):129-141. |
入库方式： OAI收割
来源：数学与系统科学研究院
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