کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5129361 | 1489645 | 2017 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Testing block-diagonal covariance structure for high-dimensional data under non-normality
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آنالیز عددی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Testing block-diagonal covariance structure for high-dimensional data under non-normality Testing block-diagonal covariance structure for high-dimensional data under non-normality](/preview/png/5129361.png)
چکیده انگلیسی
In this article, we propose a test for making an inference about the block-diagonal covariance structure of a covariance matrix in non-normal high-dimensional data. We prove that the limiting null distribution of the proposed test is normal under mild conditions when its dimension is substantially larger than its sample size. We further study the local power of the proposed test. Finally, we study the finite-sample performance of the proposed test via Monte Carlo simulations. We demonstrate the relevance and benefits of the proposed approach for a number of alternative covariance structures.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 155, March 2017, Pages 305-316
Journal: Journal of Multivariate Analysis - Volume 155, March 2017, Pages 305-316
نویسندگان
Yuki Yamada, Masashi Hyodo, Takahiro Nishiyama,