A Matrix Variance Inequality for k-Functions
DOI:
https://doi.org/10.11113/matematika.v23.n.383Abstract
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.Downloads
Published
01-06-2007
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Section
Analysis and Algebra
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Copyright of articles that appear in MATEMATIKA: MJIAM belongs exclusively to Penerbit UTM Press, Universiti Teknologi Malaysia. This copyright covers the rights to reproduce the article, including reprints, electronic reproductions or any other reproductions of similar nature.How to Cite
A Matrix Variance Inequality for k-Functions . (2007). MATEMATIKA, 23, 1-8. https://doi.org/10.11113/matematika.v23.n.383
















