Journal of Applied Mathematics and Physics
Vol.04 No.04(2016), Article ID:65447,7 pages
10.4236/jamp.2016.44070
Schur Convexity and the Dual Simpson’s Formula
Yaowen Li
Department of Mathematics, Nanjing University, Nanjing, China



Received 20 December 2015; accepted 6 April 2016; published 13 April 2016
ABSTRACT
In this paper, we show that some functions related to the dual Simpson’s formula and Bullen- Simpson’s formula are Schur-convex provided that f is four-convex. These results should be compared to that of Simpson’s formula in Applied Math. Lett. (24) (2011), 1565-1568.
Keywords:
Schur Convexity, 4-Convex Function, Dual Simpson’s Formula, Bullen-Simpson’s Formula

1. Introduction
Schur convexity is an important notion in the theory of convex functions, which were introduced by Schur in 1923 ([1] [2]), its definition is stated in what follows. Let
be denoted as,
,
and
be defined by,

Then we recall (see, e.g., [3]-[5]) that a function
is Schur convex if

Every Schur-convex function
is a symmetric function, and if I is an open interval and
is symmetric and of class
, then f is Schur-convex if and only if
(1.1)
for all
.
Let
be a convex function defined on the interval I of real numbers and
with
. The following inequality
(1.2)
holds. This double inequality is called Hermite-Hadamard inequality for convex functions. Hermite-Hadamard inequality is improved though Schur convexity, c.f., [6]-[10]. Among these paper, it is proven that if
is an interval and
is continuous, then f is convex if and only if the mapping
(Here and what follows, we use the mapping convention 




is Schur convex. Some exciting results on Schur’s majorization inequality can be found in [11]-[13].
Let 

which is called Simpson’s formula, c.f. [14] and [15]. For 




is Schur-convex, this is an improvement of the Simpson’s formula.
On the other hand, the dual Simpson’s formula ([14]) is stated as follows: if 


In [16], Bullen proved that, if f is four-convex, then the dual Simpson’s quadrature formula is more accurate than Simpson’s formula. That is, it holds that
provided that f is four-convex.
Now we can state our main results. In view of the dual Simpson’s formula and the above Bullen-Simpson formula, we construct two mappings as follows: for
We shall show that if 


2. Main Results
We now present our main theorem.
Theorem 2.1. Let 
(a) The function 

(b) The function 

(c) The function 

(d) For any 


(e) For any 


(f) For any 


(g) The function f is four-convex on I.
Proof:
The equivalence of (a) (d) (g) was already proven in [15]. Suppose that item (g) holds, then by the definition of the function


(by Simpson’s formula (1.4) and four-convexity of f) hence,
Here we denote




Now suppose that item (b) holds. Since


Next we prove item (e) implies item (g). By item (e) and the dual Simpson’s formula (1.6), we get

Since


Since
Lemma 2.1. Let 



Proof:
We only prove the first inequality. Denote that

and that


Here,


From the Hermite-Hadamard inequality for convex function




Take integration w.r.t y, we get

applying this inequality in



Now we continue the proof of our main theorem. By the definition of
here 
Suppose that item (g) holds, by applying the lemma to f in



Remark 2.1. From Lemma 2.1, we add the two inequalities together to see that the following holds for four- convex functions f:

it is well-known, c.f., [14] or [15].
Starting from this inequality (2.2), we deduce some properties for four-convex functions. As in the above, we define a pair of mappings 


Then we have
Theorem 2.2. Let 

Proof:
We observe that


Here inequality (2.3) is due to inequality (2.2), and inequality (2.4) is a consequence of the Hermite-Hada- mard inequality for convex function



Since 

It is shown in [7] for a convex function g that the function


is Schur-convex, specially we have


Furthermore, we give a Schur-convexity theorem for the following mapping:

Theorem 2.3. Let 


Proof: We observe that

Since 


Remark 2.2. For smooth four-convex functions, we see that both 



Remark 2.3. For positive real numbers x, y, we denote the arithmetic mean, geometric mean, and logarithmic mean of x, y by A, G, L. Applying non-negativity of 




Acknowledgements
The author is partially supported by the National Natural Science Foundation of China No-11071112.
Cite this paper
Yaowen Li, (2016) Schur Convexity and the Dual Simpson’s Formula. Journal of Applied Mathematics and Physics,04,623-629. doi: 10.4236/jamp.2016.44070
References
- 1. Hardy, G.H., Littlewood, J.E. and Pólya, G. (1929) Some Simple Inequalities Satisfied by Convex Functions. Messenger of Mathematics, 58, 145-152.
- 2. Schur, I. (1923) übereine Klasse von Mittelbildungenmit Anwendungen auf die Determi-nantentheorie. Sitzunsber. Berlin. Math. Ges, 22, 9-20.
- 3. Borwein, J.M. and Lewis, A.S. (2000) Convex Analysis and Nonlinear Optimization. Theory and Examples, CMS Books in Mathematics/Ouvrages de Mathématiques de la SMC, Vol. 3, Springer-Verlag, New York.
- 4. Roberts, A.W. and Varberg, D.E. (1973) Convex Functions, Pure and Applied Mathematics. Vol. 57, Academic Press, New York.
- 5. Zhang, X.M. (1998) Optimization of Schur-Convex Functions. Math. Inequal. Appl., 1, 319-330. http://dx.doi.org/10.7153/mia-01-31
- 6. Chu, Y., Wang, G. and Zhang, X. (2010) Schur-Convex and Hadmard Inequality. Math. Inequal. Appl., 13, 725-731.
- 7. Čuljak, V., Franjić, I., Ghulam, R. and Pečarić, J. (2011) Schur-Convexity of Aver-ages of Convex Functions. J. Inequal. Appl., Article ID: 581918. http://dx.doi.org/10.1155/2011/581918
- 8. Elezović, N. and Pečarić, J. (2000) A Note on Schur-Convex Functions. Rocky Mountain J. Math., 30, 853-856. http://dx.doi.org/10.1216/rmjm/1021477248
- 9. Merkle, M. (1998) Conditions for Convexity of a Derivative and Some Applications to the Gamma Function. Aequationes Math., 55, 273-280. http://dx.doi.org/10.1007/s000100050036
- 10. Zhang, X. and Chu, Y. (2010) Convexity of the Integral Mean of a Convex Function. Rocky Mountain J. Math, 40, 1061-1068. http://dx.doi.org/10.1216/RMJ-2010-40-3-1061
- 11. Hwang, F.K. and Rothblum, U.G. (2004/05) Partition-Optimization with Schur Convex Sumobjective Functions. SIAM J. Discrete Math, 18, 512-524. http://dx.doi.org/10.1137/S0895480198347167
- 12. Marshall, A.W. and Olkin, I. (1979) Inequalities: Theory of Majorization and Its Applications. Mathematics in Science and Engineering, Vol. 143, Academic Press, New York.
- 13. Steele, J.M. (2004) The Cauchy-Schwarz Master Class. An Introduction to the Art of Mathematical Inequalities. Cambridge University Press, Cambridge. http://dx.doi.org/10.1017/CBO9780511817106
- 14. Dedić, Lj., Matić, M. and Pečarić, J. (2001) On Euler Trapezoid Formulae. Appl. Math. Comput, 123, 37-62. http://dx.doi.org/10.1016/S0096-3003(00)00054-0
- 15. Franjić, I. and Pečarić, J. (2011) Schur-Convexity and the Simpson Formula. Applied Math. Lett, 24, 1565-1568. http://dx.doi.org/10.1016/j.aml.2011.03.047
- 16. Bullen, P.S. (1978) Error Estimates for Some Elementary Quadrature Rules. Univ. Beograd. Publ. Elektrotehn. Fak., Ser. Mat. Fiz. (No. 602-623), 97-103.
















