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Abstract Details
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Activity Number:
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672
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #305254 |
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Title:
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Hypothesis Testing for the Mean Vector in High Dimension
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Author(s):
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Edgard Maboudou*+
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Companies:
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Address:
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5660 Elmhurst Circle, Oviedo, FL, 32765-4119, United States
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Keywords:
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Kronecker structure ;
Separable covariance matrix ;
Sequential Monte Carlo test
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Abstract:
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We consider a test for the mean vector of independent and identically distributed multivariate normal random vectors where the dimension p is larger than or equal to the number of observations n. We propose a new test statistic based on a non-singular estimate of the covariance matrix to perform the testing. As the distribution of the statistic proposed is hard to derive, conclusions about the test are obtained by using sequential Monte Carlo procedure.
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Authors who are presenting talks have a * after their name.
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