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Register a new userHigh dimensional precision matrix estimation under weak sparsity
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Added by
Zeyu Wu
Publication date
2021
fields
Mathematical Statistics
and research's language is
English
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In this paper, we estimate the high dimensional precision matrix under the weak sparsity condition where many entries are nearly zero. We study a Lasso-type method for high dimensional precision matrix estimation and derive general error bounds under the weak sparsity condition. The common irrepresentable condition is relaxed and the results are applicable to the weak sparse matrix. As applications, we study the precision matrix estimation for the heavy-tailed data, the non-paranormal data, and the matrix data with the Lasso-type method.
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