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Chebyshev type inequalities by means of copulas
Journal of Inequalities and Applications volume 2017, Article number: 272 (2017)
Abstract
A copula is a function which joins (or ‘couples’) a bivariate distribution function to its marginal (one-dimensional) distribution functions. In this paper, we obtain Chebyshev type inequalities by utilising copulas.
1 Introduction
A copula is a function which joins (or ‘couples’) a bivariate distribution function to its marginal (one-dimensional) distribution functions. Mathematically defined, a copula C is a function \(C:[0,1]^{2}\to[0,1]\) with the following properties:
-
(C1)
\(C(u,0)=C(0,u)=0\), \(C(u,1)=u\), and \(C(1,u)=u\) for all \(u\in[0,1]\),
-
(C2)
\(C(u_{1},v_{1})-C(u_{1},v_{2})-C(u_{2},v_{1})+C(u_{2},v_{2})\geq0\) for every \(u_{1},u_{1},v_{1},v_{2} \in[0,1]\) such that \(u_{1} \leq u_{2}\) and \(v_{1} \leq v_{2}\).
Property (C2) is referred to as the 2-increasing property, or moderate growth [1]. The 2-increasing property implies the following properties for any copula C:
-
(C4)
C is nondecreasing in each variable;
-
(C5)
C satisfies the Lipschitz condition: for all \(u_{1},u_{2},v_{1},v _{2}\in[0,1]\),
$$\bigl\vert C(u_{2},v_{2})-C(u_{1},v_{1}) \bigr\vert \leq \vert u_{2}-u_{1}\vert +\vert v_{2}-v_{1}\vert . $$
For further reading on copulas, we refer the readers to [2] and [3].
While copulas join probability distributions, t-norms join membership functions of fuzzy sets, and hence combining probabilistic information and combining fuzzy information are not so different [4]. Mathematically defined, a t-norm T is a function \(T:[0,1]^{2}\rightarrow [0,1]\) with the properties [4]:
-
(T1)
Commutativity: \(T(x,y)=T(y,x)\) for all \(x,y\in[0,1]\),
-
(T2)
Associativity: \(T(x,T(y,z))=T(T(x,y),z)\) for all \(x,y,z\in[0,1]\),
-
(T3)
Monotonicity: \(T(x,y)\leq T(x,z)\) for all \(x,y,z\in[0,1]\) with \(y\leq z\),
-
(T4)
Boundary condition: \(T(x,1)=T(1,x)=x\), \(T(x,0)=T(0,x)=x\) for all \(x\in[0,1]\).
A copula is a t-norm if and only if it is associative; conversely, a t-norm is a copula if and only if it is 1-Lipschitz [1]. The three main continuous t-norms, namely the minimum operator (\(M(x,y)= \min\{x,y\}\)), the algebraic product (\(P(x,y)=xy\)), and the Lukasiewicz t-norm (\(W(x,y)=\max\{x+y-1,0\}\)), are copulas.
The first importance of these copulas is given by the following: Let C be a copula, then
The above inequality is referred to as the Fréchet-Hoeffding bounds for copulas and provides a basic inequality for copulas. Inequality (1.1) also holds in the contexts of probability theory and fuzzy probability calculus [1] and is referred to as the Bell inequalities. Further inequalities for copulas of Bell type are given in [1]. Other inequalities for copulas are given in [5] in relation to a family of continuous functions L from \([0,\infty]\times[0,\infty]\) onto \([0,\infty]\) which are nondecreasing in each variable with \(\lim_{x\rightarrow\infty}L(x,x)= \infty\).
Egozcue et al. [6] established Grüss type bounds for covariances by assuming the dependence structures such as quadrant dependence and quadrant dependence in expectation. They utilise copulas to illustrate these dependent structures.
In the same spirit to [6], it is our aim here to establish inequalities by utilising copulas. Firstly, we note the connection between the 2-increasing property and the Chebyshevian mappings. A mapping \(F:[a,b]^{2}\rightarrow\mathbb{R}\) is called Chebyshevian on \([a,b]^{2}\) if the following inequality is satisfied:
Let C be a copula, \(x,y\in[0,1]\), and set \(u_{1}=u_{2}=x\) and \(v_{1}=v_{2}=y\) in property (C2) (2-increasing property) above to obtain \(C(x,x)-C(x,y)-C(y,x)+C(y,y)\geq0\), or equivalently,
i.e. C is Chebyshevian on \([0,1]^{2}\).
Dragomir and Crstici [7] established the relationship between two synchronous functions and Chebyshevian mappings. Two functions \(f,g:[a,b]\rightarrow\mathbb{R}\) are synchronous on \([a,b]\) if they have the same monotonicity, that is,
The relationship between the two notions is given in the following result.
Proposition 1
(Dragomir and Crstici [7])
If f, g are synchronous on \([a,b]\) and \(F:[a,b]^{2}\rightarrow \mathbb{R}\), where \(F(x,y)=f(x)g(y)\), then F is Chebyshevian on \([a,b]^{2}\).
Consequently, the following Chebyshev type inequalities can be stated (see also Lehmann [8, Lemma 2]).
Proposition 2
(Dragomir and Crstici [7])
Let \(p:[a,b]\rightarrow\mathbb{R}\) be integrable and nonnegative on \([a,b]\).
-
(1)
Let \(F:[a,b]^{2}\rightarrow\mathbb{R}\). If F is Chebyshevian on \([a,b]^{2}\), then
$$ \int_{a}^{t}p(x)\,dx \int_{a}^{t} p(x)F(x,x)\,dx\geq \int_{a}^{t} \int_{a}^{t}p(x)p(y)F(x,y)\,dx \,dy $$(1.3)for all \(t\in[a,b]\).
-
(2)
Let \(f,g:[a,b]\rightarrow\mathbb{R}\) be integrable on \([a,b]\). If f and g are synchronous on \([a,b]\), then we have Chebyshev’s inequality
$$ \int_{a}^{t}p(x)\,dx \int_{a}^{t} p(x)f(x)g(x)\,dx\geq \int_{a}^{t}p(x)f(x)\,dx \int_{a}^{t}p(x)g(x)\,dx $$(1.4)for all \(t\in[a,b]\).
If \(f,g:[a,b]\rightarrow[0,1]\) are synchronous, then by Proposition 1, the product copula given by
is Chebyshevian on \([a,b]^{2}\), as a consequence of the 2-increasing property. If we define a function \(F:[a,b]^{2}\rightarrow[0,1]\) by \(F(x,y)=P(f(x),g(y))=f(x)g(y)\), and if \(p:[a,b]\rightarrow\mathbb{R}\) is integrable and nonnegative, then Proposition 2 gives us
Motivated by this observation, we aim to obtain other types of Chebyshev inequalities by utilising (the general definition of) copulas instead of the product copula as demonstrated above. Specifically, we provide inequalities for the dispersion of a function f defined on a measure space \((\Omega, \Sigma, \mu)\), with respect to a positive weight ω on Ω with \(\int_{\Omega}\omega(t)\,d\mu(t)=1\), that is,
2 Chebyshev type inequalities
The 2-increasing property of copulas gives us the following result.
Proposition 3
Let \(C:[0,1]^{2}\rightarrow[0,1]\) be a copula and \(p:[0,1]\rightarrow \mathbb{R}\) be an integrable function. Then
-
(1)
C is Chebyshevian on \([0,1]^{2}\).
-
(2)
If p is nonnegative, then
$$\int_{0}^{t}p(x)\,dx \int_{0}^{t}p(x)C(x,x)\,dx \geq \int_{0}^{t} \int_{0}^{t} p(x)p(y)C(x,y)\,dx \,dy. $$
Proof follows by (1.2) and Proposition 2 part 1.
Now we state a more general form of this inequality. We start with the following lemma.
Lemma 1
Let \(f,g:[a,b]\rightarrow[0,1]\) be two synchronous functions and C be a copula. Then \(F:[a,b]^{2}\rightarrow[0,1]\) defined by
is Chebyshevian on \([a,b]^{2}\).
Proof
Since f and g are synchronous, they have the same monotonicity on \([a,b]\). Let A be the collection of subsets of \([a,b]\) where f and g are both nondecreasing. Suppose that \(x,y\in A\). Without loss of generality, let \(x\leq y\), and set
Thus, \(u_{1} \leq u_{2}\) and \(v_{1} \leq v_{2}\) since f and g are nondecreasing. Therefore, the 2-increasing property of C gives
Suppose that \(x,y\in[a,b]\setminus A\). Without loss of generality, let \(x\leq y\),
Thus, \(u_{1} \leq u_{2}\) and \(v_{1} \leq v_{2}\) since f and g are decreasing. Therefore, the 2-increasing property of C gives
We show that F is Chebyshevian in both cases. □
Lemma 1 and Proposition 2 part 1 give us the following.
Theorem 1
Let C be a copula, \(f,g:[a,b]\rightarrow[0,1]\) be two synchronous functions, \(p:[a,b]\rightarrow\mathbb{R}\) be an integrable function. If p is nonnegative, then
Example 1
In this example, we obtain some Chebyshev type inequalities by choosing some examples of copulas. Let \(f,g:[a,b]\rightarrow[0,1]\) be two synchronous functions, and \(p:[a,b]\rightarrow\mathbb{R}\) be a nonnegative integrable function. Theorem 1 and (1.1) give us the following inequalities:
The first inequality follows from Theorem 1 (by choosing the W copula) and the rest follows from the Fréchet-Hoeffding bound (1.1). Similarly, we have
The last inequality follows from Theorem 1 (by choosing the M copula), and the rest follows from the Fréchet-Hoeffding bounds (1.1).
In what follows, we generalise Theorem 1 and Example 1.
Theorem 2
Let \((\Omega, \Sigma, \mu)\) be a measure space, \(f:\Omega\rightarrow [0,1]\) be a measurable function, and C be a copula. Then \(F:\Omega ^{2}\rightarrow[0,1]\) defined by
is Chebyshevian on \(\Omega^{2}\). We also have, for a nonnegative integrable function \(p:\Omega\rightarrow\mathbb{R}\),
Proof
The Chebyshevian property of F follows from the 2-increasing property of copulas. Therefore, we have \(F(x,x)+F(y,y)\geq F(x,y)+F(y,x)\) for all \(x,y \in\Omega\), or equivalently
Multiplying both sides by \(p(x)\) and \(p(y)\) and taking double integrals over \(\Omega^{2}\), we have
This completes the proof. □
Example 2
In this example, we obtain some Chebyshev type inequalities by choosing some examples of copulas. Let \((\Omega, \Sigma, \mu)\) be a measure space, \(f:\Omega\rightarrow[0,1]\) be a measurable function, and \(p:\Omega\rightarrow\mathbb{R}\) be a nonnegative integrable function. We have the following inequalities:
and
We also have the following result.
Theorem 3
Let \((\Omega, \Sigma, \mu)\) be a measure space, \(f:\Omega\rightarrow [0,1]\) be a measurable function. Let ω be a positive weight on Ω with \(\int_{\Omega}\omega(t)\,d\mu(t)=1\). Let \(C:[0,1]^{2} \rightarrow[0,1]\) be a copula. We have the following inequalities:
Proof
The 2-increasing property of copulas gives us
for all \(x,y \in[0,1]\). Take \(x=f(t)\) and \(y=\int_{\Omega}w(t)f(t)\, d\mu(t)\), we have
Multiplying with \(\omega(t)\geq0\) and integrating over Ω give the desired result. □
In the next section, we provide further inequalities of this type.
3 More inequalities
We denote the following:
where \(\omega:\Omega\rightarrow[0,\infty)\) is μ-integrable with \(\int_{\Omega}\omega\,d\mu=1\), \(f,g:\Omega\rightarrow[0,1]\) are μ-measurable and \(f,g\in L_{\omega}(\Omega)\), and \(C:[0,1]^{2} \rightarrow[0,1]\) is a copula.
We denote by \(D_{\omega}(f)\) the dispersion of a function f defined on a measure space \((\Omega, \Sigma, \mu)\), with respect to a positive weight ω on Ω with \(\int_{\Omega}\omega(t)\, d\mu(t)=1\), that is,
Theorem 4
Let \((\Omega, \Sigma, \mu)\) be a measure space, \(f,g:\Omega\rightarrow [0,1]\) be measurable functions. Let ω be a positive weight on Ω with \(\int_{\Omega}\omega(t)\,d\mu(t)=1\). Let \(C:[0,1]^{2} \rightarrow[0,1]\) be a copula. We have the following inequalities:
Proof
Firstly, we have
From the Lipschitz property of copulas, we have
Multiplying with \(\omega(x)\omega(y)\geq0\) and integrating twice over Ω give
Finally, Schwarz’s inequality gives
that is,
This completes the proof. □
Corollary 1
Let \((\Omega, \Sigma, \mu)\) be a measure space, \(f,g:\Omega\rightarrow [0,1]\) be measurable functions. Let ω be a positive weight on Ω with \(\int_{\Omega}\omega(t)\,d\mu(t)=1\). Let \(C:[0,1]^{2} \rightarrow[0,1]\) be a copula. If f and g satisfy
then we have the inequalities
The proof follows from Theorem 4 and a Grüss type inequality
for f with the property that \(0\leq m\leq f\leq M\leq1\). We omit the details.
Recall the notation
and introduce the following notation:
Theorem 5
Let \(\omega:\Omega\rightarrow[0,\infty)\) be μ-integrable with \(\int_{\Omega}\omega\,d\mu=1\). Let \(f,g:\Omega\rightarrow[0,1]\) be μ-measurable and \(f,g\in L_{ \omega}(\Omega)\). If \(C:[0,1]^{2}\rightarrow[0,1]\) is a copula, then
In particular, we have
We also have
In particular,
Proof
We know that for any μ-ω-integrable functions k and l, we have
and
Using the Fréchet-Hoeffding bounds (1.1), we obtain
for all \(x,y\in\Omega\). If we multiply (3.8) by \(w(x)w(y)\geq0\) and integrate twice over Ω, then we get
and
This proves (3.2). We obtain (3.3) by setting \(f\equiv g\) in (3.2).
From (1.1), we also have
If we multiply (3.10) by \(w\geq0\) and integrate over Ω, then we get
Since
and
By (3.11), (3.12), and (3.13), we get (3.4). Finally, we obtain (3.5) by setting \(f\equiv g\) in (3.4). □
Lemma 2
If \(C:[0,1]^{2} \rightarrow[0,1]\) is a copula, then we have
for any \(u,v\in[0,1]\).
Proof
Using the Fréchet-Hoeffding bounds (1.1) and the fact that
thus we have
for any \(u,v\in[0,1]\). This inequality is equivalent to
Applying the reverse triangle inequality, we have
for any \(u,v\in[0,1]\). Similarly,
for any \(u,v\in[0,1]\). Therefore,
giving that
for all \(u,v\in[0,1]\). From (3.15), we then obtain
for all \(u,v\in[0,1]\). □
Consider the quantities
and
By the properties of modulus, we have
and
By Schwarz’s inequality, we also have
and
We have the following result.
Theorem 6
Let \(\omega: \Omega\rightarrow[0,\infty)\) be μ-integrable with \(\int_{\Omega}\omega \,d\mu=1\). Let \(f,g: \Omega\rightarrow[0,1]\) be μ-measurable and such that \(f,g\in L_{\omega}(\Omega)\). If \(C:[0,1]^{2}\rightarrow[0,1]\) is a copula, then (with the notation in Theorem 5), we have
In particular, we have
We also have
In particular, we have
Proof
From Lemma 2 we have
for any \(x,y\in\Omega\). We multiply (3.21) by \(\omega(x)\omega(y)\geq0\) and integrate to get
Again, from Lemma 2 we have
If we multiply (3.22) by \(\omega\geq0\) and integrate, then we get
We obtain the particular cases by setting \(f \equiv g\). □
Remark 1
We denote the following quantities:
Some particular instances of interest:
-
(a)
Let \(\Omega=[0,1]\), \(\omega:[0,1]\rightarrow[0,\infty)\), \(\int_{0}^{1}\omega(t)\,dt=1\), \(f(t)=g(t)=t\) \((t\in[0,1])\). Then by (3.3) we get
$$\begin{aligned} \max\biggl\{ 2 \int_{0}^{1}t\omega(t)\,dt-1,0 \biggr\} \leq& \int_{0} ^{1} \int_{0}^{1}\omega(x)\omega(y)C(x,y)\,dx \,dy \\ =:&K_{\omega}(C) \leq \int_{0}^{1}t\omega(t)\,dt, \end{aligned}$$that is,
$$\max\{2E_{\omega}-1,0\}\leq K_{\omega}(C)\leq E_{\omega}. $$By Theorem 6, we have
$$\begin{aligned} \frac{1}{2}I_{\omega}\leq E_{\omega}-K_{\omega}(C)\leq \frac{1}{2}I _{\omega}+\frac{1}{2}- \int_{0}^{1}\omega(t)\biggl\vert \frac{1}{2}-t\biggr\vert \,dt\leq\frac{1}{2}I_{\omega}+ \frac{1}{2} \end{aligned}$$and
$$\begin{aligned} \frac{1}{2}H_{\omega}\leq E_{\omega}-L_{\omega}(C)\leq \frac{1}{2}H _{\omega}+\frac{1}{2}- \int_{0}^{1}\omega(t)\biggl\vert \frac{1}{2}-t\biggr\vert \,dt\leq\frac{1}{2}H_{\omega}+ \frac{1}{2}. \end{aligned}$$ -
(b)
Take \(\Omega=[0,1]\), \(\omega(t)=1\) \((t\in[0,1])\) to get
$$\begin{aligned}& \max\biggl\{ \int_{0}^{1}f(t)\,dt+ \int_{0}^{1}g(t)\,dt-1,0 \biggr\} \\& \quad \leq \int_{0}^{1} \int_{0}^{1}C\bigl(f(x),g(y)\bigr)\,dx \,dy \\& \quad \leq \min\biggl\{ \int_{0}^{1}f(t)\,dt, \int_{0}^{1}g(t)\,dt \biggr\} . \end{aligned}$$When \(f\equiv g\), we get
$$\begin{aligned} \max\biggl\{ 2 \int_{0}^{1}f(t)\,dt-1,0 \biggr\} \leq \int_{0}^{1} \int_{0}^{1}C\bigl(f(x),f(y)\bigr)\,dx \,dy \leq \int_{0}^{1}f(t)\,dt. \end{aligned}$$By Theorem 6, we have
$$\begin{aligned}& \frac{1}{2} \int_{\Omega} \int_{\Omega}\bigl\vert f(x)-g(y)\bigr\vert \,d\mu(x)\,d\mu(y) \\& \quad \leq \frac{1}{2} \biggl( \int_{\Omega}f \,d\mu+ \int_{\Omega}g \,d\mu\biggr) - \int_{\Omega} \int_{\Omega}C\bigl(f(x), g(y)\bigr)\,d\mu(x)\,d\mu(y) \\& \quad \leq \frac{1}{2} \int_{\Omega} \int_{\Omega}\bigl\vert f(x)-g(y)\bigr\vert \,d\mu(x)\,d\mu(y)+ \frac{1}{2}-\max\biggl\{ \int_{\Omega}\biggl\vert \frac{1}{2}-f\biggr\vert \,d\mu, \int_{\Omega}\biggl\vert \frac{1}{2}-g\biggr\vert \,d\mu \biggr\} \\& \quad \leq \frac{1}{2} \int_{\Omega} \int_{\Omega}\bigl\vert f(x)-g(y)\bigr\vert \,d\mu(x)\,d\mu(y)+ \frac{1}{2}. \end{aligned}$$When \(f\equiv g\), we have
$$\begin{aligned}& \frac{1}{2} \int_{\Omega} \int_{\Omega}\bigl\vert f(x)-f(y)\bigr\vert \,d\mu(x)\,d\mu(y) \\& \quad \leq \int_{\Omega}f \,d\mu- \int_{\Omega} \int_{\Omega}C\bigl(f(x), f(y)\bigr)\,d\mu(x)\,d\mu(y) \\& \quad \leq \frac{1}{2} \int_{\Omega} \int_{\Omega}\bigl\vert f(x)-f(y)\bigr\vert \,d\mu(x)\,d\mu(y)+ \frac{1}{2}- \int_{\Omega}\biggl\vert \frac{1}{2}-f\biggr\vert \,d\mu \\& \quad \leq \frac{1}{2} \int_{\Omega} \int_{\Omega}\bigl\vert f(x)-f(y)\bigr\vert \,d\mu(x)\,d\mu(y)+ \frac{1}{2}. \end{aligned}$$We also have
$$\begin{aligned}& \int_{\Omega}\biggl\vert f- \int_{\Omega}g \,d\mu\biggr\vert \,d\mu \\& \quad \leq \frac{1}{2} \biggl( \int_{\Omega}f \,d\mu+ \int_{\Omega}g \,d\mu\biggr) - \int_{\Omega}C \biggl( f, \int_{\Omega}g \,d\mu\biggr)\,d\mu \\& \quad \leq \int_{\Omega}\biggl\vert f- \int_{\Omega}g \,d\mu\biggr\vert \,d\mu+ \frac{1}{2}-\max \biggl\{ \int_{\Omega}\biggl\vert \frac{1}{2}-f\biggr\vert \,d\mu, \biggl\vert \frac{1}{2}- \int_{\Omega}g \,d\mu\biggr\vert \biggr\} \\& \quad \leq \int_{\Omega}\biggl\vert f- \int_{\Omega}g \,d\mu\biggr\vert \,d\mu+ \frac{1}{2}, \end{aligned}$$and
$$\begin{aligned} \int_{\Omega}\biggl\vert f- \int_{\Omega}f \,d\mu\biggr\vert \,d\mu \leq& \int_{\Omega}f \,d\mu- \int_{\Omega}C \biggl( f, \int_{\Omega}f \,d\mu\biggr)\,d\mu \\ \leq& \int_{\Omega}\biggl\vert f- \int_{\Omega}f \,d\mu\biggr\vert \,d\mu+ \frac{1}{2}- \int_{\Omega}\biggl\vert \frac{1}{2}-f\biggr\vert \,d\mu \\ \leq& \int_{\Omega}\biggl\vert f- \int_{\Omega}f \,d\mu\biggr\vert \,d\mu+ \frac{1}{2}. \end{aligned}$$
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Acknowledgements
The research of E Kikianty is supported in part by the National Research Foundation of South Africa (Grant Number 109297) and University of Pretoria’s Research Development Programme.
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Dragomir, S.S., Kikianty, E. Chebyshev type inequalities by means of copulas. J Inequal Appl 2017, 272 (2017). https://doi.org/10.1186/s13660-017-1549-y
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DOI: https://doi.org/10.1186/s13660-017-1549-y