Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9741772 | Journal of Statistical Planning and Inference | 2005 | 8 Pages |
Abstract
In the course of solving a variational problem Chernoff (Ann. Probab. 9 (1981) 533) obtained what appears to be a specialized inequality for a variance, namely, that for a standard normal variable X, Var[g(X)]⩾E[gâ²(X)]2. However, both the simplicity and usefulness of the inequality has generated a plethora of extensions, as well as alternative proofs. All previous papers have focused on a single function. We provide here an inequality for the covariance matrix of k functions, which leads to a matrix inequality in the sense of Loewner.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Ingram Olkin, Larry Shepp,