Proving Inequality for Convex Functions with Given Conditions

In summary, the given statement is to prove that for all non-negative real numbers a and b, the sum of the function f at a and b is greater than or equal to the function evaluated at the sum of a and b. This can be proved by using the definition of a convex function and the given conditions that the second derivative of the function is greater than or equal to 0 and the function evaluated at 0 is equal to 0. By applying the property that f is convex if and only if for all x and y in the real numbers and for all lambda between 0 and 1, f of lambda x plus 1 minus lambda y is less than or equal to lambda times f of x plus 1 minus lambda
  • #1
Contingency
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Homework Statement


Givens: [tex]\forall x\ge 0:\quad f^{ \prime \prime }\left( x \right) \ge 0;\quad f\left( 0 \right) =0[/tex]
Prove: [tex]\forall a,b\ge 0:\quad f\left( a+b \right) \ge f\left( a \right) +f\left( b \right)[/tex]

Homework Equations


By definition, f is convex iff [tex]\forall x,y\in \Re \quad \wedge \quad \forall \lambda :\quad 0\le \lambda \le 1\quad \Rightarrow \quad f\left( \lambda x+(1-\lambda )y \right) \le \lambda f\left( x \right) +(1-\lambda )f\left( y \right)[/tex]

The Attempt at a Solution


Intuition-wise I see that a convex function's values increase at an increasing rate, but that's equivalent to [tex]f^{ \prime \prime }\left( x \right) \ge 0[/tex]
I also see that [tex]f\left( 0 \right) =0[/tex] is necessary for the inequality to hold, but I can't find any tools with which I can work on proving the inequality.
Also I figure [tex]\forall x\ge 0:\quad f^{ \prime }\left( x \right) \ge 0[/tex] and also monotonously increasing.
 
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  • #2
OK, so we wish to prove that a convex function is "superadditive".

First, can you prove that if [itex]t\in [0,1][/itex], that then

[tex]f(tx)\leq tf(x)[/tex]

Just apply convexity and use that f(0)=0.
 
  • #3
alright, that's immediate from taking y=0.
So I now know that [tex]f(\lambda x)\leq \lambda f(x)[/tex]
 
  • #4
Now write

[tex]f(a)+f(b)=f\left(\frac{a}{a+b}(a+b)\right)+f\left(\frac{b}{a+b}(a+b) \right)[/tex]

and apply that inequality you just obtained.
 
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  • #5
just figured that bit out
thanks alot!
 
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What is a convex function?

A convex function is a type of mathematical function that has a graph that curves upward and is always "bowed" towards the ground, meaning that any line segment drawn between two points on the graph will always be above the graph itself. This type of function is commonly found in optimization and economics problems, and can be represented by a parabola or other similar curves.

What is a convex function inequality?

A convex function inequality is an inequality that involves a convex function. It states that for any two points on a convex function, the value of the function at the midpoint of the two points will always be less than or equal to the average of the values at the two points. In other words, the function will always be "bowed" towards the ground and will never "curve" towards the sky.

How is a convex function inequality used in real life?

Convex function inequalities have many real-life applications, such as in economics, where they are used to model consumer behavior and production functions. They are also used in optimization problems, such as finding the minimum cost for a given set of constraints, and in machine learning, where they are used to minimize the error in a model.

What is the relationship between convexity and concavity?

Convexity and concavity are two opposite properties of functions. A function is convex if its graph curves upward and is "bowed" towards the ground, while a function is concave if its graph curves downward and is "bowed" towards the sky. In other words, a convex function inequality states that the function will always be "bowed" towards the ground, while a concave function inequality states that the function will always be "bowed" towards the sky.

How is convexity tested for a function?

To test for convexity, one can use the second derivative test. If the second derivative of a function is always positive, then the function is convex. Another method is to check if the function satisfies the convex function inequality for any two points. If it does, then the function is convex. Additionally, convexity can also be tested by plotting the graph of the function and visually inspecting if it is "bowed" towards the ground.

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