Abstract
We present in this paper a necessary and sufficient condition to establish the inequality between generalized weighted means which share the same sequence of numbers but differ in the weights. We first present a sufficient condition, and then obtain the more general, necessary and sufficient, condition. Our results were motivated by an inequality, involving harmonic means, found in the study of multiple importance sampling Monte Carlo technique. We present new proofs of Chebyshev’s sum inequality, Cauchy-Schwartz, and the rearrangement inequality, and derive several interesting inequalities, some of them related to the Shannon entropy, the Tsallis, and the Rényi entropy with different entropic indices, and to logsumexp mean. Those inequalities are obtained as particular cases of our general inequality, and show the potential and practical interest of our approach. We show too the relationship of our inequality with sequence majorization.
Author supplied keywords
- Cauchy-Schwartz inequality
- Chebyshev’s sum inequality
- Rearrangement inequality
- Rényi entropy
- Tsallis entropy
- entropy
- generalized weighted mean
- inequalities
- logsumexp mean
- majorization
- weighted Kolmogorov mean
- weighted arithmetic mean
- weighted geometric mean
- weighted harmonic mean
- weighted power mean
- weighted quasi-arithmetic mean
Cite
CITATION STYLE
Sbert, M., & Poch, J. (2016). A necessary and sufficient condition for the inequality of generalized weighted means. Journal of Inequalities and Applications, 2016(1). https://doi.org/10.1186/s13660-016-1233-7
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.