A Matrix Variance Inequality for k-Functions

Authors

  • Norhayati Rosli
  • Wan Muhamad Amir Wan Ahmad

DOI:

https://doi.org/10.11113/matematika.v23.n.383

Abstract

In this paper a course of solving variational problem is considered. [2] obtained what appears to be specialized inequality for a variance, namely, that for a standard normal variable X , Var[g(x)] \ge E[g'(x)]2. However both of the simplicity and usefulness of the inequality has generated a plethora of extensions, as well as alternative proofs. [5] had focused on a result of two random variables for the normal and gamma distribution. They obtained the result of normal distribution with k functions, without proving and the proof is presented here. This paper also extend the result obtained by [5] to the k functions for the gamma distribution. Keywords: Normal Distribution; Gamma Distribution; Laguerre Family; Hermite Polynomials.

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Published

01-06-2007

How to Cite

Rosli, N., & Wan Ahmad, W. M. A. (2007). A Matrix Variance Inequality for k-Functions . MATEMATIKA, 23, 1–8. https://doi.org/10.11113/matematika.v23.n.383

Issue

Section

Mathematics