Conjecture on the global-null correlation maximum bound
Conjecture on the global-null correlation maximum bound
Let be the density of , let , and let be the cumulative distribution function of the maximum of an independent correlation matrix based on observed -vectors, scaled by . Global-null correlation maximum conjecture. For fixed ,
This conjecture is the technical bound needed to apply the correlation-limit approximation when controlling the probability that independent correlations exceed the maximum correlation of a large correlation matrix. The paper states that it is needed to prove the asymptotic exponential law under the global null, but reports that it has not yet been proved.
Sources & referencesView supporting material
Primary source
Max Grazier G'Sell, Jonathan Taylor and Robert Tibshirani, “Adaptive testing for the graphical lasso”, arXiv:1307.4765 (2013).
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