Real analysis: Problem similar to uniformly integrable

In summary, the conversation discusses a proof for \inf { \int_{E}f d\mu : E\inM, \mu(E) ≥\alpha} >0, given the assumptions \mu(X) >0 and f is a measurable function satisfying f(x) >0 for all x in X. The hint suggests proving for any \delta satisfying 0<\delta<\alpha, there exists an n \in N such that \mu(B_{n}) \geq \mu(X) - \delta, and then showing that \mu(E\capB_{n}) ≥\alpha-\delta. This can be used to show that \inf {\int_{B_{n}\cap E}f
  • #1
happysauce
42
0

Homework Statement



Assume [itex]\mu[/itex](X) >0 and that f is a measurable function that maps X into ℝ and satisfies f(x) >0 for all x[itex]\in[/itex]X.

Let [itex]\alpha[/itex] be any fixed real number satisfying 0<[itex]\alpha[/itex]<[itex]\mu[/itex](X) <infinity Prove that

inf { [itex]\int[/itex][itex]_{E}[/itex]f d[itex]\mu[/itex] : E[itex]\in[/itex]M, [itex]\mu[/itex](E) ≥[itex]\alpha[/itex]} >0.

(Hint. First prove for any [itex]\delta[/itex] satisfying 0<[itex]\delta[/itex]<[itex]\alpha[/itex], prov there exists n [itex]\in[/itex] N such that B[itex]_{n}[/itex] = {x:f(x)[itex]\geq[/itex]1/n} satisfies [itex]\mu[/itex](B[itex]_{n}[/itex]) [itex]\geq[/itex]
[itex]\mu[/itex](X) - [itex]\delta[/itex]. Then prove that if [itex]\mu[/itex](E) ≥[itex]\alpha[/itex] then [itex]\mu[/itex](E[itex]\cap[/itex]B[itex]_{n}[/itex]) ≥[itex]\alpha[/itex]-[itex]\delta[/itex]

Homework Equations



Not sure what is relevant.

The Attempt at a Solution



So, the hint suggests the first thing I do is show that given 0<[itex]\delta[/itex]<[itex]\alpha[/itex] i can find an n so that [itex]\mu[/itex](B[itex]_{n}[/itex]) [itex]\geq[/itex] [itex]\mu[/itex](X) - [itex]\delta[/itex]. So since f(x) >0 then [itex]\mu[/itex](X) = [itex]\mu[/itex]({x:f(x)>0}) = [itex]\mu[/itex]({x:f(x)≥1/n} [itex]\cup[/itex]{x:f(x)<1/n}). These are disjoint so we have [itex]\mu[/itex]({x:f(x)≥1/n}) + [itex]\mu[/itex]({x:f(x)<1/n}). If i show the delta relation with [itex]\mu[/itex]({x:f(x)<1/n}) then i get [itex]\mu[/itex](B[itex]_{n}[/itex]) [itex]\geq[/itex] [itex]\mu[/itex](X) - [itex]\delta[/itex]. It seems really trivial though and I am not sure what guarantees this.

The next part asks you to show that [itex]\mu[/itex](E[itex]\cap[/itex]B[itex]_{n}[/itex]) ≥[itex]\alpha[/itex]-[itex]\delta[/itex]. Ok so [itex]\mu[/itex](E[itex]\cap[/itex]B[itex]_{n}[/itex]) = [itex]\mu[/itex](E) +[itex]\mu[/itex](B[itex]_{n}[/itex]) - [itex]\mu[/itex](E[itex]\cup[/itex]B[itex]_{n}[/itex])

The following hold: [itex]\mu[/itex](E[itex]\cup[/itex]B[itex]_{n}[/itex]) ≤[itex]\mu[/itex](X) (both are subsets)
[itex]\mu[/itex](B[itex]_{n}[/itex]) ≥ [itex]\mu[/itex](X) - [itex]\delta[/itex] (previous part)
[itex]\mu[/itex](E)≥[itex]\alpha[/itex] (hypothesis)

So [itex]\mu[/itex](E[itex]\cap[/itex]B[itex]_{n}[/itex]) = [itex]\mu[/itex](E) +[itex]\mu[/itex](B[itex]_{n}[/itex]) - [itex]\mu[/itex](E[itex]\cup[/itex]B[itex]_{n}[/itex]) ≥ [itex]\mu[/itex](X) - [itex]\delta[/itex] + [itex]\mu[/itex](E) - [itex]\mu[/itex](X) =[itex]\mu[/itex](E)- [itex]\delta[/itex]≥[itex]\alpha[/itex]-[itex]\delta[/itex]


So I've done most of what the hint wants... the problem is I don't know how this helps me.
 
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  • #2
The title is misleading, I thought it related to uniformly intagrable but I don't think it does.
 
  • #3
I figured out why there is an n for every δ. So I figured out both parts of the hint, but I still have no clue how to make these hints help me here. Do I have to show that

inf {[itex]\int[/itex][itex]_{B_{n}\cap E}[/itex]f d[itex]\mu[/itex], E[itex]\in[/itex]M, [itex]\mu (B_{n}\cap E)[/itex]≥α-δ} > 0 for each n? And then as n-> infinity we have the desired result? I'm still not sure how to prove this case though...
 

1. What is real analysis?

Real analysis is a branch of mathematics that deals with the study of real-valued functions and sequences. It focuses on understanding the properties and behavior of these functions and sequences, including convergence, continuity, and differentiability.

2. What is a uniformly integrable function?

A uniformly integrable function is a type of real-valued function that meets certain criteria for its integrability. Specifically, it is a function whose integral can be approximated arbitrarily well by the integrals of a class of simpler functions. This property is useful in various areas of mathematics, including probability theory and measure theory.

3. What is the importance of studying uniformly integrable functions?

Uniformly integrable functions play a crucial role in various areas of mathematics, including probability theory and measure theory. They provide a way to approximate more complex functions and make calculations and proofs more manageable. Understanding their properties can also lead to important insights and results in these fields.

4. What are some examples of uniformly integrable functions?

Some examples of uniformly integrable functions include continuous functions, bounded functions, and functions that are integrable on a compact interval. Other examples can be constructed by combining simpler uniformly integrable functions, such as by taking linear combinations or products.

5. What are some applications of uniformly integrable functions?

Uniformly integrable functions have various applications in mathematics, including probability theory, measure theory, and functional analysis. They are also useful in understanding the behavior of other types of functions, such as Lebesgue integrable functions. Additionally, the concept of uniform integrability can be extended to other structures, such as vector spaces and topological spaces, making it a versatile tool in mathematical analysis.

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