• Corpus ID: 235358761

Superconsistency of Tests in High Dimensions

@inproceedings{Kock2021SuperconsistencyOT,
  title={Superconsistency of Tests in High Dimensions},
  author={Anders Kock and David Preinerstorfer},
  year={2021}
}
To assess whether there is some signal in a big database, aggregate tests for the global null hypothesis of no effect are routinely applied in practice before more specialized analysis is carried out. Although a plethora of aggregate tests is available, each test has its strengths but also its blind spots. In a Gaussian sequence model, we study whether it is possible to obtain a test with substantially better consistency properties than the likelihood ratio (i.e., Euclidean norm based) test. We… 

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