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Ridge estimation of covariance matrix from data in two classes

Yi ZhouBin Zhang — 2024

Applications of Mathematics

This paper deals with the problem of estimating a covariance matrix from the data in two classes: (1) good data with the covariance matrix of interest and (2) contamination coming from a Gaussian distribution with a different covariance matrix. The ridge penalty is introduced to address the problem of high-dimensional challenges in estimating the covariance matrix from the two-class data model. A ridge estimator of the covariance matrix has a uniform expression and keeps positive-definite, whether...

Chebyshev bounds for Beurling numbers

Harold G. DiamondWen-Bin Zhang — 2013

Acta Arithmetica

The first author conjectured that Chebyshev-type prime bounds hold for Beurling generalized numbers provided that the counting function N(x) of the generalized integers satisfies the L¹ condition 1 | N ( x ) - A x | d x / x 2 < for some positive constant A. This conjecture was shown false by an example of Kahane. Here we establish the Chebyshev bounds using the L¹ hypothesis and a second integral condition.

Optimality of Chebyshev bounds for Beurling generalized numbers

Harold G. DiamondWen-Bin Zhang — 2013

Acta Arithmetica

If the counting function N(x) of integers of a Beurling generalized number system satisfies both 1 x - 2 | N ( x ) - A x | d x < and x - 1 ( l o g x ) ( N ( x ) - A x ) = O ( 1 ) , then the counting function π(x) of the primes of this system is known to satisfy the Chebyshev bound π(x) ≪ x/logx. Let f(x) increase to infinity arbitrarily slowly. We give a construction showing that 1 | N ( x ) - A x | x - 2 d x < and x - 1 ( l o g x ) ( N ( x ) - A x ) = O ( f ( x ) ) do not imply the Chebyshev bound.

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