Prove inequality of a convex function

In summary, to prove the inequality of a convex function, one typically demonstrates that for any two points \(x\) and \(y\) in its domain and any \(t\) in the interval [0, 1], the following holds: \(f(tx + (1-t)y) \leq tf(x) + (1-t)f(y)\). This involves showing that the line segment connecting the points \((x, f(x))\) and \((y, f(y))\) lies above the graph of the function \(f\). The proof may leverage the definition of convexity, properties of derivatives, or Jensen's inequality, depending on the context and the specific function being analyzed.
  • #1
Lambda96
223
75
Homework Statement
Proof that the following inequality holds ##\frac{f(x_2)-f(x_1)}{x_2-x_1} \leq \frac{f(x_3)-f(x_1)}{x_3-x_1 } \leq \frac{f(x_3)-f(x_2)}{x_3-x_2}##
Relevant Equations
none
Hi,

I have problem to prove that the following inequality holds

Bildschirmfoto 2024-05-01 um 21.21.01.png

I thought of the following, since it is a convex function and ##x_1 < x_2 <x_3## applies, I started from the following inequality ##f(x_2) \leq f(x_3)## and transformed it further

$$f(x_2) \leq f(x_3)$$
$$f(x_2)-f(x_1) \leq f(x_3)-f(x_1)$$
$$\frac{f(x_2)-f(x_1)}{x_2- x_1} \leq \frac{f(x_3)-f(x_1)}{x_2 - x_1}$$

Since the following applies ##x_2 - x_1 \leq x_3 - x_1## it follows ##\frac{f(x_3)-f(x_1)}{x_3- x_1} \leq \frac{f(x_3)-f(x_1)}{x_2 - x_1}## then follows ##\frac{f(x_2)-f(x_1)}{x_2- x_1} \leq \frac{f(x_3)-f(x_1)}{x_3 - x_1}## i.e. the first part of the inequality

Is my approach correct, or does anyone have a better idea of how I can prove the inequality?
 
Physics news on Phys.org
  • #2
##f(x_2)\leq f(x_3)## sounds like a condition about increasing functions, not convex functions. What is the definition of a convex function?

Also note your last step is wrong, you basically wrote down ##a<b## and ##c< b## and concluded ##a<c##
 
  • Like
Likes Lambda96 and FactChecker
  • #3
## f ## is convex if and only if
[tex]
\frac{f(y)-f(x)}{y-x} \leqslant \frac{f(z)-f(x)}{z-x}
[/tex]
for all ## a < x < y < z < b ##. You have arrived to the right conclusion, but it does not stem from monotonicity (##x^2## is convex but not monotone, for instance) nor the suspect step in between. Consider instead
[tex]
f(y) \leqslant \frac{z-y}{z-x}f(x)+\frac{y-x}{z-x}f(z).
[/tex]
  1. Why is this inequality true? (substitute ## y=(1-\lambda)x + \lambda z ##)
  2. Check that it is equivalent to the first inequality.
 
Last edited:
  • Like
Likes Lambda96
  • #4
Thank you Office_Shredder and nuuskur for your help 👍👍

Since it is a convex function and ##x_2## lies between ##x_1## and ##x_3##, I can represent ##x_2## as follows ##x_2=(1- \lambda)x_1 + \lambda x_3## with ##\lambda \in (0,1)##

I then inserted this expression into the first part of the inequality ##\frac{f(x_2)-f(x_1)}{x_2-x_1} \leq \frac{f(x_3)-f(x_1)}{x_3-x_1 }##

In order to get the required inequality, I applied the following, since it is a convex function ##f((1- \lambda)x_1 + \lambda x_3) \le (1-\lambda)f(x_1) + \lambda f(x_3)##
 
  • Like
Likes nuuskur

FAQ: Prove inequality of a convex function

What is a convex function?

A convex function is a real-valued function defined on an interval or a convex set, where the line segment between any two points on the graph of the function lies above or on the graph itself. Mathematically, a function f is convex if for any two points x and y in its domain and for any t in [0, 1], the following holds: f(tx + (1-t)y) ≤ tf(x) + (1-t)f(y).

Why is proving the inequality of a convex function important?

Proving the inequality of a convex function is important because it establishes the fundamental properties of convexity, which have significant implications in optimization, economics, and various fields of mathematics. These inequalities can help in finding minima and maxima, ensuring that certain solutions are optimal, and understanding the behavior of the function over its domain.

What are some common inequalities associated with convex functions?

Some common inequalities associated with convex functions include Jensen's inequality, which states that for a convex function f and a set of weights summing to 1, f of the weighted average is less than or equal to the weighted average of f. Another important inequality is the second derivative test, where a twice-differentiable function is convex if its second derivative is non-negative over its domain.

How can I prove that a function is convex?

To prove that a function is convex, you can use several methods: one common approach is to show that its second derivative is non-negative (if the function is twice differentiable). Alternatively, you can verify the definition of convexity by showing that for any two points x and y in the domain, the inequality f(tx + (1-t)y) ≤ tf(x) + (1-t)f(y) holds for all t in [0, 1].

Can you provide an example of proving an inequality for a convex function?

Certainly! Consider the function f(x) = x², which is convex. To prove Jensen's inequality for f, take two points a and b, and weights t and 1-t (where t ∈ [0, 1]). We need to show that f(ta + (1-t)b) ≤ tf(a) + (1-t)f(b). Calculating, we have f(ta + (1-t)b) = (ta + (1-t)b)² and tf(a) + (1-t)f(b) = t(a²) + (1-t)(b²). Expanding the left side and simplifying shows that the inequality holds, confirming that f(x) = x² satisfies Jensen's inequality and is convex.

Similar threads

Replies
2
Views
1K
Replies
6
Views
961
Replies
8
Views
1K
Replies
3
Views
1K
Replies
8
Views
2K
Replies
1
Views
1K
Back
Top