How to Prove the Measure Property for a Nonnegative Measurable Function?

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Homework Help Overview

The discussion revolves around proving the measure property for a nonnegative measurable function within the context of measure theory. The original poster presents a problem involving a measure space and seeks to establish that a defined measure \(\nu\) satisfies certain properties related to integration.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants explore the application of the definition of a measure to \(\nu\) and suggest using the monotone convergence theorem. There are attempts to show the equality of integrals for non-negative measurable functions based on previously established results for simple functions. Questions arise regarding the validity of certain equalities and whether inequalities should be considered.

Discussion Status

Some participants have provided guidance on starting points, such as considering step functions and approximations. The discussion includes various interpretations and approaches to the problem, with no explicit consensus reached on the method to be used.

Contextual Notes

Participants mention the use of specific textbooks and definitions of integrals for non-negative functions, indicating that different approaches may depend on the definitions used in their respective resources.

Kindayr
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Homework Statement


Let [itex](X,\mathcal{B},\mu)[/itex] be a measure space and [itex]g[/itex] be a nonnegative measurable function on [itex]X[/itex]. Set [itex]\nu (E)=\int_{E}g\,d\mu[/itex]. Prove that [itex] \nu[/itex] is a measure and [tex]\int f\, d \nu =\int fg\,d\mu[/tex] for all nonnegative measurable functions [itex]f[/itex] on [itex]X[/itex].

The Attempt at a Solution


I'm basically at a total loss on how to start this. I'll keep working on it tonight, and will add to it as I go.
 
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Have you tried applying the definition of "measure" to [itex]\nu[/itex]? You'll have to use some basic results, like the monotone convergence theorem, to get stuff to work out.
 
I've shown for non-negative simple functions that [tex]\int \phi\,d\nu=\int \phi g \,d\mu.[/tex] Now I wish to show it in general for non-negative measurable functions. So I say let [itex]f[/itex] be a non-negative measurable function on X. Fix [itex]\phi[/itex] as a simple function such that [itex]0\le\phi \le f[/itex]. Hence we have [itex]\int \phi\,d\nu=\int \phi g \,d\mu[/itex], and thus [tex]\int f\, d\nu=\sup_{\phi} \int \phi \, d\,\nu=\sup_{\phi} \int g\phi\, d\,\mu \overset{?}{=} \int gf\, d\mu.[/tex]

Am I allowed to make that last equality?
 
Should I do some inequalities for simple functions above and below? I feel like that last equality should be an inequality. Hrmf.
 
Kindayr said:

Homework Statement


Let [itex](X,\mathcal{B},\mu)[/itex] be a measure space and [itex]g[/itex] be a nonnegative measurable function on [itex]X[/itex]. Set [itex]\nu (E)=\int_{E}g\,d\mu[/itex]. Prove that [itex] \nu[/itex] is a measure and [tex]\int f\, d \nu =\int fg\,d\mu[/tex] for all nonnegative measurable functions [itex]f[/itex] on [itex]X[/itex].



The Attempt at a Solution


I'm basically at a total loss on how to start this. I'll keep working on it tonight, and will add to it as I go.

Try it first for step functions f, of the form
[tex]f = \sum_{i=1}^n c_i \chi(I_i),[/tex] where [itex]I_1, I_2,..., I_n[/itex] is a measurable partition of [itex]R[/itex] and [itex]\chi(A)[/itex] is the characteristic function of a set [itex]A \subset R: \: \chi(A)(x) = 0 \text{ if } x \not\in A, \text{ and } \chi(A)(x) = 1 \text{ if } x \in A.[/itex]

RGV
 
Ray Vickson said:
Try it first for step functions f, of the form
[tex]f = \sum_{i=1}^n c_i \chi(I_i),[/tex] where [itex]I_1, I_2,..., I_n[/itex] is a measurable partition of [itex]R[/itex] and [itex]\chi(A)[/itex] is the characteristic function of a set [itex]A \subset R: \: \chi(A)(x) = 0 \text{ if } x \not\in A, \text{ and } \chi(A)(x) = 1 \text{ if } x \in A.[/itex]

RGV

Hey, thanks for the reply!

I've already done this for simple functions, I'm just stuck on how to show that any non-negative measurable function satisfies the equality. Should i take approximations from above and below? or should what I gave in my first reply be sufficient?
 
Kindayr said:
Hey, thanks for the reply!

I've already done this for simple functions, I'm just stuck on how to show that any non-negative measurable function satisfies the equality. Should i take approximations from above and below? or should what I gave in my first reply be sufficient?

I don't know how your textbook defines the integral for general functions, but many treatments define it as the limit of integrals of step functions.

RGV
 
Ray Vickson said:
I don't know how your textbook defines the integral for general functions, but many treatments define it as the limit of integrals of step functions.

RGV

I'm using Royden, where the integral of a non-negative function is defined as
[tex]\int f\, d\,\mu =\sup \{\int \phi \, d\mu :0\le\phi\le f,\,\phi \, simple\}[/tex]
 
So my question is if I'm allowed to say this:
[tex]\int f\, d\nu = \sup \{\int \phi\, d\nu :0\le\phi\le f,\, \phi \,simple\} =\sup \{\int \phi g\,d\mu :0\le\phi\le f,\,\phi\,simple\} = \int fg\,d\mu?[/tex]
 
  • #10
Nevermind, I'll just use Monotone Convergence on a sequence of simple functions.
 

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