A two-sample test for high-dimension, low-sample-size data under the strongly spiked eigenvalue model
نویسندگان
چکیده
منابع مشابه
Largest Eigenvalue Estimation for High-Dimension, Low-Sample-Size Data and its Application
A common feature of high-dimensional data is the data dimension is high, however, the sample size is relatively low. We call such data HDLSS data. In this paper, we study HDLSS asymptotics when the data dimension is high while the sample size is fixed. We first introduce two eigenvalue estimation methods: the noise-reduction (NR) methodology and the cross-data-matrix (CDM) methodology. We show ...
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ژورنال
عنوان ژورنال: Hiroshima Mathematical Journal
سال: 2017
ISSN: 0018-2079
DOI: 10.32917/hmj/1509674448