2021
DOI: 10.48550/arxiv.2108.06892
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Mean Test with Fewer Observation than Dimension and Ratio Unbiased Estimator for Correlation Matrix

Tiefeng Jiang,
Ping Li

Abstract: Hotelling's T-squared test is a classical tool to test if the normal mean of a multivariate normal distribution is a specified one or the means of two multivariate normal means are equal. When the population dimension is higher than the sample size, the test is no longer applicable. Under this situation, in this paper we revisit the tests proposed by Srivastava and Du (2008), who revise the Hotelling's statistics by replacing Wishart matrices with their diagonal matrices. They show the revised statistics are a… Show more

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Cited by 3 publications
(6 citation statements)
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References 32 publications
(45 reference statements)
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“…Part (i) of Theorem S6 is from Srivastava and Du (2008). Recently Jiang and Li (2021) obtained a general theory, which also leads to the same conclusion. Same as in the onesample test, for test T…”
Section: Discussionsupporting
confidence: 53%
See 3 more Smart Citations
“…Part (i) of Theorem S6 is from Srivastava and Du (2008). Recently Jiang and Li (2021) obtained a general theory, which also leads to the same conclusion. Same as in the onesample test, for test T…”
Section: Discussionsupporting
confidence: 53%
“…Part (i) of the above theorem is from Srivastava (2009), which is also a corollary of the recent work by Jiang and Li (2021). For the sum-type test, a level-α test will be performed through rejecting H 0 when T…”
Section: σ2mentioning
confidence: 95%
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“…Feng et al (2017) assumed a block diagonal structure for the covariance matrix, and within each block, Hotelling's T 2 can be applied. Further studies on DHT include, for example, Srivastava (2009), Park and Ayyala (2013), Srivastava et al (2013), Feng and Sun (2015), , Gregory et al (2015), Dong et al (2016), Cao et al (2018), Chen et al (2019), and Jiang and Li (2021).…”
Section: Introductionmentioning
confidence: 99%