On a method of construction of new means with applications
© Raïssouli and Sándor; licensee Springer 2013
Received: 25 August 2012
Accepted: 17 January 2013
Published: 5 March 2013
In the present paper, we would like to introduce a simple transformation for bivariate means from which we derive a lot of new means. Relationships between the standard means are also obtained. A simple link between the Stolarsky mean and the Gini mean is given. As applications, this transformation allows us to extend some means from two to three or more arguments.
1 Introduction and basic notions
In the recent past, the theory of means has been the subject intensive research. It has proved to be a useful tool for theoretical viewpoint as well as for practical purposes. For the definition of a mean, various statements, more or less different, can be found in the literature; see  and the references therein. Throughout this paper, we adopt the following definition.
and are known as the arithmetic, geometric, harmonic, logarithmic, identric, weighted geometric, contraharmonic and (first) Seiffert means, respectively.
A mean m is symmetric if and homogeneous if for all . The above means are all symmetric and homogeneous. However, the mean is (homogeneous) not symmetric, while is (symmetric) not homogeneous. The mean is neither symmetric nor homogeneous.
A mean m is called monotone if is increasing in a and in b, that is, if (resp. ), then (resp. ). There are many means which are not monotone. For example, it is easy to see that the means A, G, H, L are monotone but C is not. However, extending the above definitions of reflexivity and monotonicity from a mean to a general binary map, the following result is of interest [2, 3].
Proposition 1.1 Let m be a monotone and reflexive map. Then m is a mean.
For a given mean m, we set , and it is easy to see that is also a mean, called the dual mean of m. If m is homogeneous, then so is with . If m is symmetric and homogeneous, then so is , and in this case, we have . Every mean m satisfies , and if and are two means such that , then . One can check that and . Further, the arithmetic and harmonic means are mutually dual (i.e., , ) and the geometric mean is self-dual (i.e., ). The dual of the logarithmic and identric means has been studied by the second author in .
Remark 1.1 Let be a monotone continuous function and denote by its inverse function. An extension of the dual mean can be given by . It is easy to verify that is a mean. For , we obtain the classical dual. If we choose with , then we get the following generalized dual . If m is symmetric and homogeneous, then .
Let m be a homogeneous mean. Writing , we then associate to m a unique positive function f defined by for all . The function f will be called the associated function to the mean m, or we simply say that f corresponds to the mean m. It follows that f corresponds to a homogeneous mean if and only if . Clearly, , and if, moreover, m is symmetric, then for every . It is obvious that a mean m is monotone if and only if its associated function is increasing. For example, the contraharmonic mean C is not monotone because its associated function satisfies , and it is easy to see that f is not increasing for all , but only for .
Now, let us observe the next question : under which sufficient condition a given function f is the associated function of a certain mean? The following result gives an answer to this situation; see , Remark 12.
Proposition 1.2 Let be a function such that for every . Then defines a (homogeneous) mean. If, moreover, f is increasing with for each , then m is monotone symmetric.
Proposition 1.3 Let m be a symmetric and homogeneous mean having a strictly increasing associated function f. Then , the associated function to the dual mean , is strictly increasing, too.
By virtue of the relation (and so ), the result of the above proposition is in fact an equivalence. It follows that the associated function of the dual will be not always increasing since that of C is not.
2 A mean-transformation
Summarizing the above, we may state the following.
which we call the t-transformation of m.
We explicitly notice that the convergence of the infinite product in (3) is shown by the double inequality (2).
The elementary properties of the mean-transformation are summarized in the next result.
is a mean.
- (ii)If m is homogeneous (resp. symmetric, monotone), then so is and the associated function to is given by
for each , where denotes the generalized dual mean (see Remark 1.1).
- (ii)The symmetry of from that of m is obvious, while the monotonicity of follows from the fact that m is monotone and is defined as (infinite) product of positive terms. Now, assume that m is homogeneous. By definition, we have for all
The homogeneity of follows since .
- (iii)By definition, we have successively
and (v) are not difficult. Details are omitted for the reader as a simple exercise. □
We now present the following examples. In all these examples, the sequence is as in the above.
Reduction of the three chains of inequalities (4), (5) and (6) in one chain does not appear to be obvious. However, for the particular case , the above three chains can be reduced into one chain; see Corollary 4.1 in Section 4 below.
The situation of this example will be developed below.
In what follows, we will explore this latter situation in more detail. For the sake of simplicity, we restrict ourselves to the case . The general case can be stated in a similar manner and we leave it to the reader. Precisely, we put the following.
Clearly, is a mean for all . The next example may be stated.
where we put for every .
we deduce that every p-increasing (resp. p-decreasing) sequence is p-convergent. This together with inequalities (7) implies that the mean-sequences , , and are decreasingly p-convergent. Then, what are their limits? The answer to this latter question will be presented in the next section after stating some needed results.
3 Study of a special case
In what follows, we will see that the mean satisfies good properties, the first of which is announced as well.
- (i)For all and , we have(9)
- (ii)Assume that m is homogeneous and let f and be the associated functions of m and , respectively. Then, for every , one has(10)
In particular (for ), we obtain .
Follows from the fact that when combined with (i). The proof is completed. □
From the above proposition, we can derive some interesting results. The first result concerns an answer to the question that has been put in the above section.
Corollary 3.1 Let m be a symmetric and homogeneous mean such that is p-convergent. Then its limit is , the geometric mean. In particular, , , and are decreasingly p-convergent to the same limit G.
It follows that , which is the associated function of G, in this way proving the first part of the proposition. For the second part, as already pointed before, the sequences , , and are p-decreasing. It follows that they p-converge and by the first part they have G as a common limit. The proof of the proposition is complete. □
Corollary 3.2 Let and be two homogeneous means such that for a certain . Then .
We deduce that for each and so , which completes the proof. □
Now, let us observe the next question: Does (9) (resp (10)) characterize for a given mean (resp. homogeneous mean) m? For the sake of simplicity, we assume that m is homogeneous and we will prove the following theorem.
Then is the associated function of defined by (8).
which, following Proposition 3.1(ii), is the associated function of , in this way proving the desired result. □
We now present some examples illustrating the above. In all these examples, r and α are such that , .
Example 3.1 Let be the associated function of G. We have , that is, for all , which has been already pointed before.
which is the associated function of . Otherwise, . In particular, with (and so ), we obtain . By Proposition 2.1, we deduce .
which is the associated function of , that is, . In particular (if , ), we find and so .
To find out if this latter function corresponds to a certain homogeneous mean for all is left to the reader. For the particular case , , the answer to this question is obviously positive since is the associated function of S. We then have and so .
The fact that this latter function is the associated function of a certain homogeneous mean does not appear to be obvious. See the section below for a general point of view.
4 Decomposable means
For the sake of convenience, for concrete examples, we may introduce the following notion.
Definition 4.1 Let m be a mean such that there exists a mean and some satisfying . Then we say that m is -decomposable. In the case , we simply say m is -decomposable.
If m is -decomposable, then for all , the generalized dual mean is -decomposable.
If m is -decomposable and is -decomposable, then for all , is -decomposable.
It is an equivalent version of Proposition 2.1(iv). □
Now, we will illustrate the above notions and results by some examples.
Example 4.1 We have already seen that for each . We say that G is self-decomposable. Also, we can see that and for every .
Example 4.2 The relationship (1), written in a brief form , says that L is A-decomposable. By Proposition 4.1(i), we deduce that is H-decomposable. We have also seen , that is, I is S-decomposable and so is -decomposable. We leave it to the reader to see that A is C-decomposable and so H is -decomposable. Other examples, in a more general point of view, will be stated below.
Example 4.3 In this example, we are interested in the link between two double-power means, namely the Stolarsky and Gini means. By virtue of this interest, we state its content as an explicit result from which we will derive some interesting consequences.
holds for all real numbers p and q.
This latter function is that associated to , that is, . The proof is completed. □
Since , Proposition 2.1(iii) yields . The desired inequalities follow by combining the two above chains of inequalities.
in this way proving the desired aim. □
Theorem 4.1 contains more new applications: some extensions for can imply analogous ones for . See Section 5 below for more details concerning this latter situation.
We leave to the reader the routine task of formulating further examples in the aim to obtain some links between other special means.
Now, a question arises naturally from the above: Is it true that every mean is -decomposable? In other words, let m be a given mean, do a mean and a real number such that exist? The answer to this latter question appears to be interesting. In fact, for reason of simplicity, assume that m is homogeneous and we search for a homogeneous mean such that . According to Proposition 3.1, it is equivalent to have for all , where f denotes the associated function of the given mean m and g will be that of the unknown mean . That is to say, the function is the associated function to a certain mean for some . Combining this with Proposition 1.2, we can state the next result, which gives an answer to the above question.
There exists a homogeneous mean such that m is -decomposable, that is, .
The function is the associated function of a certain homogeneous mean.
- (iii)The following inequalities:
hold for every , with reversed inequalities for each .
then the homogeneous mean is symmetric and monotone.
The following corollary is immediate from the above proposition when combined with Proposition 1.2.
m is -decomposable.
g is the associated function of a certain mean.
- (iii)The double inequality
holds for all , with reversed inequalities for each .
then is a symmetric and monotone mean.
Corollary 4.3 Let m be a (symmetric) homogeneous monotone mean and let be a given real number. Then there exists a homogeneous mean such that m is -decomposable. In particular, every (symmetric) homogeneous monotone mean m is -decomposable for some homogeneous mean .
for every , with reversed inequalities if . By virtue of the above proposition, we can conclude the first part of the announced result. Taking , , we obtain the second part and thus complete the proof. □
In the above corollary, we explicitly notice that the mean m should be monotone in order to ensure that m is -decomposable for some mean , but is not necessary monotone. As an example, we have already seen that A is C-decomposable with A monotone but C is not monotone.
Example 4.5 The standard means A, H, G, L, I are all (symmetric) homogeneous and monotone, then we find again that these means are decomposable. However, as already pointed before, the contraharmonic mean C is not monotone and so we cannot apply the above corollary. Let us try to apply directly Proposition 4.2. We can easily verify that the associated function of C does not satisfy (iii) and so C is not decomposable.
We leave it to the reader to check if the means S and P are decomposable or not.
The reader can easily verify that all the above standard means A, H, G, L, I, P, C, S satisfy relationship (15). However, for the corresponding functions g, it is not always monotone as in the case for A and H. In the general case, the following result gives a sufficient condition for ensuring the increase monotonicity of g.
Proposition 4.3 Let m be a symmetric homogeneous monotone mean and f be its associated function. Suppose that the function is strictly increasing. Then the function will be strictly increasing.
Proof One has , where . Since is decreasing, we get that k is increasing. Since is strictly increasing, we get that g is strictly increasing (as a product of an increasing and a strictly increasing positive functions). □
Example 4.6 The means G and L satisfy the conditions of the above proposition, whereas the means A and H do not. This rejoins the fact that A is C-decomposable and H is -decomposable with C and not monotone means. We leave it to the reader to verify if the means I and P satisfy or not the conditions of the above proposition.
5 Application: means with several arguments
In this section, we investigate an application of our above theoretical study. This application turns out the extension of some means from two variables to three or more arguments.
The following result is well known in the literature.
hold true for all distinct real numbers .
It is also simple to see that for all .
can be considered as a definition of the logarithmic mean with several variables. Now, the fact that if this definition coincides or not with some other ones as these given in [8, 10–12] seems to be an interesting problem. We omit the details about this latter point which is beyond our aim here.
To give more justification for our above extensions, the following result, which extends the inequalities from two variables to several arguments, may be stated.
hold for all distinct real numbers .
Proof For the sake of simplicity, we write (16) in a brief form . According to (17), we easily show that . Since , , , we then obtain . Using (17) again, a simple computation yields . The proof is complete. □
- Bullen PS Mathematics and Its Applications. In Handbook of Means and Their Inequalities. 2nd edition. Springer, Berlin; 1987.Google Scholar
- Matkowski J: Convex functions with respect to a mean and a characterization a quasi-arithmetic mean. Real Anal. Exch. 2003/2004, 29(1):220–246.MathSciNetGoogle Scholar
- Matkowski J: On weighted extension of Cauchy’s means. J. Math. Anal. Appl. 2006, 319: 215–227. 10.1016/j.jmaa.2006.01.040MathSciNetView ArticleGoogle Scholar
- Sándor J: On the identric and logarithmic means. Aequ. Math. 1990, 40: 261–270. 10.1007/BF02112299View ArticleGoogle Scholar
- Matkowski J: Iterations of the mean-type mappings. Grazer Math. Ber. 354. In ECIT’08 Edited by: Sharkovsky AN, Susko IM. 2009, 158–179.Google Scholar
- Raïssouli M: Approaching the power logarithmic and difference means by algorithms involving the power binomial mean. Int. J. Math. Math. Sci. 2011., 2011: Article ID 687825Google Scholar
- Raïssouli M: Stabilizability of the Stolarsky mean and its approximation in terms of the power binomial mean. Int. J. Math. Anal. 2012, 6(18):871–881.Google Scholar
- Mustonen, S: Logarithmic mean for several arguments. http://www.survo.fi/papers/logmean.pdf (2002)Google Scholar
- Sándor J, Trif T: A new refinement of the Ky Fan inequality. Math. Inequal. Appl. 1999, 2(4):529–533.MathSciNetGoogle Scholar
- Xiao Z-G, Zhang Z-H: The inequalities in n variables. JIPAM. J. Inequal. Pure Appl. Math. 2003., 4: Article ID 39Google Scholar
- Pittenger AO: The logarithm mean in n variables. Am. Math. Mon. 1985, 92: 99–104. 10.2307/2322637MathSciNetView ArticleGoogle Scholar
- Raïssouli M: Logarithmic functional mean in convex analysis. JIPAM. J. Inequal. Pure Appl. Math. 2009., 10(4): Article ID 102Google Scholar
- Neuman E: Stolarsky means of several variables. JIPAM. J. Inequal. Pure Appl. Math. 2005., 6(2): Article ID 30Google Scholar
- Pečarić J, Šimić V: Stolarsky-Tobey mean in n variables. Math. Inequal. Appl. 1999, 2: 325–341.MathSciNetGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.