Stats 300 C : Theory of

نویسنده

  • Karthik Rajkumar
چکیده

We have seen that the BH procedure controls the FDR for multiple testing when the p-values are independent. How can we control the FDR under dependence? Here, we consider the case where the statistics have distribution Y ∼ N (μ,Σ); in the past, we have assumed that Σ = Ip. If the covariance matrix Σ were known, we could reduce to the independent case using the transformation Y ′ = Σ− 1 2Y , so that

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Stats 300 C : Theory of Statistics Spring 2017 Lecture 25 — Jun 5 , 2017

In today’s class we will consider the above problem (1) when μ is sparse. We begin by motivating the special case of sparsity. Thereafter we show that a thraueshold estimator is optimal (in minimax sense), if the sparsity of μ is known. We then introduce FDR-threshold estimator, which is oblivious to μ’s sparsity and is yet optimal. We then draw parallel between this problem and multiplehypothe...

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تاریخ انتشار 2017