- Research Article
- Open Access
- Published:

# The Schur Harmonic Convexity of the Hamy Symmetric Function and Its Applications

*Journal of Inequalities and Applications*
**volume 2009**, Article number: 838529 (2009)

## Abstract

We prove that the Hamy symmetric function is Schur harmonic convex for . As its applications, some analytic inequalities including the well-known Weierstrass inequalities are obtained.

## 1. Introduction

Throughout this paper we use to denote the -dimensional Euclidean space over the field of real numbers, and .

For , and , we denote by

For , the Hamy symmetric function [1–3] was defined as

Corresponding to this is the *r* th order Hamy mean

where . Hara et al. [1] established the following refinement of the classical arithmetic and geometric means inequality:

Here and denote the classical arithmetic and geometric means, respectively.

The paper [4] by Ku et al. contains some interesting inequalities including the fact that is log-concave, the more results can also be found in the book [5] by Bullen. In [2], the Schur convexity of Hamy's symmetric function and its generalization were discussed. In [3] , Jiang defined the dual form of the Hamy symmetric function as follows:

discussed the Schur concavity Schur convexity of , and established some analytic inequalities.

The main purpose of this paper is to investigate the Schur harmonic convexity of the Hamy symmetric function . Some analytic inequalities including Weierstrass inequalities are established.

## 2. Definitions and Lemmas

Schur convexity was introduced by Schur in 1923 [6], and it has many important applications in analytic inequalities [7–12], linear regression [13], graphs and matrices [14], combinatorial optimization [15], information-theoretic topics [16], Gamma functions [17], stochastic orderings [18], reliability [19], and other related fields.

For convenience of readers, we recall some definitions as follows.

Definition 2.1.

A set is called a convex set if whenever . A set is called a harmonic convex set if whenever .

It is easy to see that is a harmonic convex set if and only if is a convex set.

Definition 2.2.

Let be a convex set a function is said to be convex on if for all . Moreover, is called a concave function if is a convex function.

Definition 2.3.

Let be a harmonic convex set a function is called a harmonic convex (or concave, resp.) function on if for all .

Definitions 2.2 and 2.3 have the following consequences.

Fact A.

If is a harmonic convex set and is a harmonic convex function, then

is a concave function. Conversely, if is a convex set and is a convex function, then

is a harmonic concave function.

Definition 2.4.

Let be a set a function is called a Schur convex function on if

for each pair of -tuples and in , such that , that is,

where denotes the th largest component in . is called a Schur concave function on if is a Schur convex function on .

Definition 2.5.

Let be a set a function is called a Schur harmonic convex (or concave, resp.) function on if

for each pair of and in , such that .

Definitions 2.4 and 2.5 have the following consequences.

Fact B.

Let be a set, and , then is a Schur harmonic convex (or concave, resp.) function on if and only if is a Schur concave (or convex, resp.) function on .

The notion of generalized convex function was first introduced by Aczél in [20]. Later, many authors established inequalities by using harmonic convex function theory [21–28]. Recently, Anderson et al. [29] discussed an attractive class of inequalities, which arise from the notation of harmonic convex functions.

The following well-known result was proved by Marshall and Olkin [6].

Theorem 2 A.

Let be a symmetric convex set with nonempty interior , and let be a continuous symmetric function on . If is differentiable on , then is Schur convex (or concave, resp.) on if and only if

for all and . Here, is a symmetric set means that implies for any permutation matrix .

Remark 2.6.

Since is symmetric, the Schur's condition in Theorem , that is, (2.6) can be reduced to

The following Lemma 2.7 can easily be derived from Fact, Theorem and Remark 2.6 together with elementary computation.

Lemma 2.7.

Let be a symmetric harmonic convex set with nonempty interior , and let be a continuous symmetry function on . If is differentiable on , then is Schur harmonic convex (or concave, resp.) on if and only if

for all .

Next we introduce two lemmas, which are used in Sections 3 and 4.

Lemma 2.8 ([5, page 234]).

For , if th r -th order symmetric function is defined as

then

Lemma 2.9 ([2, Lemma 2.2]).

Suppose that and . If , then

## 3. Main Result

In this section, we give and prove the main result of this paper.

Theorem 3.1.

The Hamy symmetric function is Schur harmonic convex in .

Proof.

By Lemma 2.7, we only need to prove that

To prove (3.1), we consider the following possible cases for .

Case 1 ().

Then (1.2) leads to , and (3.1) is clearly true.

Case 2 ().

Then (1.2) leads to the following identity:

and therefore, (3.1) follows from (3.2).

Case 3 ().

Then (1.2) leads to

Simple computation yields

From (3.4) we get

Therefore, (3.1) follows from (3.5) and the fact that is increasing in .

Case 4 ().

Fix and let and We have the following identity:

Differentiating (3.6) with respect to and , respectively, and using Lemma 2.8, we get

From (3.7) we obtain

Therefore, (3.1) follows from (3.8) and the fact that is increasing in .

## 4. Applications

In this section, making use of our main result, we give some inequalities.

Theorem 4.1.

Suppose that with . If and , then

Proof.

The proof follows from Theorem 3.1 and Lemma 2.9 together with (1.2).

If taking and in Theorem 4.1, respectively, then we have the following corollaries.

Corollary 4.2.

Suppose that with . If , then

Corollary 4.3.

Suppose that with . If , then

Taking in Corollaries 4.2 and 4.3, respectively, we get the following.

Corollary 4.4.

If and , then

Corollary 4.5 (Weierstrass inequalities [30, Page 260]).

If , and , then

Theorem 4.6.

If and , then

Proof.

Let , and be the -tuple, then obviously

Therefore, Theorem 4.6 follows from Theorem 3.1, (4.7) ,and (1.2).

Theorem 4.7.

Let be an -dimensional simplex in -dimensional Euclidean space , and be the set of vertices. Let be an arbitrary point in the interior of A. If is the intersection point of the extension line of and the -dimensional hyperplane opposite to the point , and , then one has

Proof.

It is easy to see that

(4.9) implies that

Therefore, Theorem 4.7 follows from Theorem 3.1, (4.10), and (1.2).

## References

Hara T, Uchiyama M, Takahasi S-E:

**A refinement of various mean inequalities.***Journal of Inequalities and Applications*1998,**2**(4):387–395. 10.1155/S1025583498000253Guan K:

**The Hamy symmetric function and its generalization.***Mathematical Inequalities & Applications*2006,**9**(4):797–805.Jiang W-D:

**Some properties of dual form of the Hamy's symmetric function.***Journal of Mathematical Inequalities*2007,**1**(1):117–125.Ku H-T, Ku M-C, Zhang X-M:

**Inequalities for symmetric means, symmetric harmonic means, and their applications.***Bulletin of the Australian Mathematical Society*1997,**56**(3):409–420. 10.1017/S0004972700031191Bullen PS:

*Handbook of Means and Their Inequalities, Mathematics and Its Applications*.*Volume 560*. Kluwer Academic Publishers, Dordrecht, The Netherlands; 2003:xxviii+537.Marshall AW, Olkin I:

*Inequalities: Theory of Majorization and Its Applications, Mathematics in Science and Engineering*.*Volume 143*. Academic Press, New York, NY, USA; 1979:xx+569.Hardy GH, Littlewood JE, Pólya G:

**Some simple inequalities satisfied by convex functions.***Messenger of Mathematics*1929,**58:**145–152.Zhang X-M:

**Schur-convex functions and isoperimetric inequalities.***Proceedings of the American Mathematical Society*1998,**126**(2):461–470. 10.1090/S0002-9939-98-04151-3Aujla JS, Silva FC:

**Weak majorization inequalities and convex functions.***Linear Algebra and Its Applications*2003,**369:**217–233.Qi F, Sándor J, Dragomir SS, Sofo A:

**Notes on the Schur-convexity of the extended mean values.***Taiwanese Journal of Mathematics*2005,**9**(3):411–420.Chu Y, Zhang X:

**Necessary and sufficient conditions such that extended mean values are Schur-convex or Schur-concave.***Journal of Mathematics of Kyoto University*2008,**48**(1):229–238.Chu Y, Zhang X, Wang G:

**The Schur geometrical convexity of the extended mean values.***Journal of Convex Analysis*2008,**15**(4):707–718.Stepniak C:

**Stochastic ordering and Schur-convex functions in comparison of linear experiments.***Metrika*1989,**36**(5):291–298.Constantine GM:

**Schur convex functions on the spectra of graphs.***Discrete Mathematics*1983,**45**(2–3):181–188. 10.1016/0012-365X(83)90034-1Hwang FK, Rothblum UG:

**Partition-optimization with Schur convex sum objective functions.***SIAM Journal on Discrete Mathematics*2004,**18**(3):512–524. 10.1137/S0895480198347167Forcina A, Giovagnoli A:

**Homogeneity indices and Schur-convex functions.***Statistica*1982,**42**(4):529–542.Merkle M:

**Convexity, Schur-convexity and bounds for the gamma function involving the digamma function.***The Rocky Mountain Journal of Mathematics*1998,**28**(3):1053–1066. 10.1216/rmjm/1181071755Shaked M, Shanthikumar JG, Tong YL:

**Parametric Schur convexity and arrangement monotonicity properties of partial sums.***Journal of Multivariate Analysis*1995,**53**(2):293–310. 10.1006/jmva.1995.1038Hwang FK, Rothblum UG, Shepp L:

**Monotone optimal multipartitions using Schur convexity with respect to partial orders.***SIAM Journal on Discrete Mathematics*1993,**6**(4):533–547. 10.1137/0406042Aczél J:

**A generalization of the notion of convex functions.***Det Kongelige Norske Videnskabers Selskabs Forhandlinger, Trondheim*1947,**19**(24):87–90.Vamanamurthy MK, Vuorinen M:

**Inequalities for means.***Journal of Mathematical Analysis and Applications*1994,**183**(1):155–166. 10.1006/jmaa.1994.1137Roberts AW, Varberg DE:

*Convex Functions, Pure and Applied Mathematics*.*Volume 5*. Academic Press, New York, NY, USA; 1973:xx+300.Niculescu CP, Persson L-E:

*Convex Functions and Their Applications. A Contemporary Approach, CMS Books in Mathematics/Ouvrages de Mathématiques de la SMC, 23*. Springer, New York, NY, USA; 2006:xvi+255.Matkowski J:

**Convex functions with respect to a mean and a characterization of quasi-arithmetic means.***Real Analysis Exchange*2004,**29**(1):229–246.Bullen PS, Mitrinović DS, Vasić PM:

*Means and Their Inequalities, Mathematics and Its Applications (East European Series)*.*Volume 31*. D. Reidel, Dordrecht, The Netherlands; 1988:xx+459.Das C, Mishra S, Pradhan PK:

**On harmonic convexity (concavity) and application to non-linear programming problems.***Opsearch*2003,**40**(1):42–51.Das C, Roy KL, Jena KN:

**Harmonic convexity and application to optimization problems.***The Mathematics Education*2003,**37**(2):58–64.Kar K, Nanda S:

**Harmonic convexity of composite functions.***Proceedings of the National Academy of Sciences, Section A*1992,**62**(1):77–81.Anderson GD, Vamanamurthy MK, Vuorinen M:

**Generalized convexity and inequalities.***Journal of Mathematical Analysis and Applications*2007,**335**(2):1294–1308. 10.1016/j.jmaa.2007.02.016Bullen PS:

*A Dictionary of Inequalities, Pitman Monographs and Surveys in Pure and Applied Mathematics*.*Volume 97*. Longman, Harlow, UK; 1998:x+283.

## Acknowlegments

This research is partly supported by N S Foundation of China under Grant 60850005 and N S Foundation of Zhejiang Province under Grants D7080080 and Y607128.

## Author information

### Authors and Affiliations

### Corresponding author

## Rights and permissions

**Open Access** This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## About this article

### Cite this article

Chu, Y., Lv, Y. The Schur Harmonic Convexity of the Hamy Symmetric Function and Its Applications.
*J Inequal Appl* **2009**, 838529 (2009). https://doi.org/10.1155/2009/838529

Received:

Accepted:

Published:

DOI: https://doi.org/10.1155/2009/838529

### Keywords

- Convex Function
- Symmetric Function
- Concave Function
- Nonempty Interior
- Dimensional Euclidean Space