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

In summary, homework statement:Let (X, \mathcal{B}, \mu) be a measure space and g be a nonnegative measurable function on X. Set \nu (E)=\int_{E}g\,d\mu. Prove that \nu is a measure and \int f\, d \nu =\int fg\,d\mu for all nonnegative measurable functions f on X.
  • #1
Kindayr
161
0

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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  • #2
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.
 
  • #3
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?
 
  • #4
Should I do some inequalities for simple functions above and below? I feel like that last equality should be an inequality. Hrmf.
 
  • #5
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
 
  • #6
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?
 
  • #7
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
 
  • #8
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]
 
  • #9
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.
 

1. What is measure theory?

Measure theory is a branch of mathematics that deals with the concept of measuring sets and their properties. It provides a rigorous framework for defining and analyzing measures, which are used to quantify the size or extent of a set.

2. What are the basic concepts of measure theory?

The basic concepts of measure theory include sets, measures, measurable functions, and measures of integration. Sets are collections of objects, measures are functions that assign a numerical value to a set, measurable functions are functions with well-defined measures, and measures of integration are used to calculate the integral of a function.

3. What are some applications of measure theory?

Measure theory has many applications in various fields of mathematics, such as probability theory, functional analysis, and differential geometry. It is also used in physics, economics, and engineering to model and analyze real-world phenomena.

4. What is the importance of measure theory in mathematics?

Measure theory is an important branch of mathematics as it provides a rigorous foundation for many other areas of mathematics, including analysis, probability, and topology. It also has applications in various other fields, making it a fundamental tool for understanding and solving problems in these areas.

5. What are some common examples of measures?

Some common examples of measures include length, area, volume, and probability. These measures can be applied to various sets, such as line segments, rectangles, cubes, and events in probability. Other examples include measures of similarity, such as the Lebesgue measure and Hausdorff measure, which are used in geometry and fractal analysis.

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