When Does Measurability Hold in Product Space?

In summary, the conversation discusses the measurability in a product space and how it is affected by the dependency of the second component on the first component. It is stated that for fixed t, the set T_0\times \Omega_t is measurable and this is proven using Fubini's theorem. The book by Doob on stochastic process is mentioned and the conclusion is that the dependence of the second component on the first does not affect the measurability condition in a product space as long as the second component is measurable for each fixed t.
  • #1
wayneckm
68
0
Hello all,


I have some difficulty in determining the measurability in product space. Suppose the product space is [itex]T \times \Omega [/itex] equipped with [itex] \mathcal{T} \otimes \mathcal{F}[/itex] where [itex] ( T , \mathcal{T} , \mu ), ( \Omega , \mathcal{F} , P)[/itex] are themselves measurable spaces.

Now, if there exists a set [itex] T_0 [/itex] in [itex] T [/itex] with [itex] \mu(T_{0}^{c}) =0[/itex] and, for each fixed [itex] t \in T_0 [/itex], a property holds almost everywhere in [itex] \Omega [/itex], so this means there exists a [itex] \Omega_{t} [/itex] such that [itex] P(\Omega_{t}^{c}) = 0 [/itex] and that property holds on this set.

How can we conclude that the property will holds almost everywhere in the product space [itex]T \times \Omega [/itex]? Are they saying the set [itex]T_0 \times\Omega_{t} [/itex] is measurable?

Or in other words, when does the measurability hold if the second set [itex]\Omega_{t} [/itex] is a function of the first set [itex]T_0 [/itex]?

Thanks very much.


Wayne
 
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  • #2
The set [itex]T_0\times \Omega_t[/itex] will always be measurable. By definition, since the product of measurable sets is always measurable.

But this is not what you're asking. You need to show that there is a set A of [itex]T\times \Omega[/itex] such that [itex](\mu\times P)(A^c)=0[/itex] and such that "the property" holds on A.

But what property are we talking about?? Surely this isn't true for every property...
 
  • #3
Thanks for the reply.

First of all, I want to know if the second component [itex] \Omega_t [/itex] depends on the first component [itex] T_0 [/itex], how can we show/prove its measurability?

Secondly, indeed I read this from a book, and the aurthor simply stated that "as there is [itex] T_0 [/itex] such that for each fixed [itex] t\in T_0 [/itex], the property of [itex] a(t,\omega) = b(t,\omega)"[/itex] holds almost surely, then this also holds almost everywhere on [itex] T \times \Omega [/itex], how can he jump to this conclusion?

Thanks very much.Wayne
 
  • #4
What book are you reading?

wayneckm said:
Thanks for the reply.
First of all, I want to know if the second component [itex] \Omega_t [/itex] depends on the first component [itex] T_0 [/itex], how can we show/prove its measurability?

Well, for fixed t, the set [itex]T_0\times \Omega_t[/itex] is measurable by the definition of the product sigma algebra. There's nothing much else to prove.

Secondly, indeed I read this from a book, and the aurthor simply stated that "as there is [itex] T_0 [/itex] such that for each fixed [itex] t\in T_0 [/itex], the property of [itex] a(t,\omega) = b(t,\omega)"[/itex] holds almost surely, then this also holds almost everywhere on [itex] T \times \Omega [/itex], how can he jump to this conclusion?

Recall that a=b if for each measurable set A holds that

[tex]\iint_A{(a-b)dP d\mu}=0[/tex]

Now, by Fubini's theorem, this amounts to

[tex]\int_T \int_\Omega I_A (a-b)dP d\mu = \int_{T_0} \int_\Omega (a(t,\omega)-b(t,\omega))dP d\mu[/tex]

Since for each fixed t, we have that [itex]a(t,\omega)=b(t,\omega)[/itex]. It follows that the integral is 0. Thus a=b almost everywhere.
 
  • #5
Thanks so much for the explanation!

It is the book by Doob on stochastic process, it tried to regard a stochastic process as a function of two variables.

So it is true that the dependence of second component on the first one does not affect the condition of measurability in a product space as long as for each fixed point, the second component is measurable? or in other words, the collection of [itex] ( t , f(t,\omega) ) [/itex] is a measurable set iff, for each fixed [itex] t [/itex], [itex] f(t,\omega)[/itex] is measurable in [itex] \Omega [/itex]?

Thanks!Wayne
 

FAQ: When Does Measurability Hold in Product Space?

1. What is meant by "measurability" in product space?

Measurability in product space refers to the ability to accurately quantify and evaluate the performance and effectiveness of a product or service in the market. This includes measuring factors such as sales, customer satisfaction, and market share.

2. Why is measurability important for businesses?

Measurability allows businesses to track their progress and success in the market, identify areas for improvement, and make data-driven decisions. It also helps businesses to compare their performance with competitors and adapt their strategies accordingly.

3. How is measurability achieved in product space?

Measurability is achieved through the use of various metrics and data analysis techniques. This can include sales data, customer feedback, market research, and other key performance indicators. Advanced technologies such as data analytics and artificial intelligence are also used to improve measurability.

4. What are the challenges in achieving measurability in product space?

One of the main challenges in achieving measurability in product space is identifying and collecting relevant data. This can be a time-consuming and complex process, especially for businesses with a wide range of products and services. Another challenge is ensuring the accuracy and reliability of the data collected.

5. How can businesses improve their measurability in product space?

To improve measurability, businesses should establish clear and measurable goals, regularly track and analyze data, and use a variety of metrics to get a comprehensive view of their performance. It is also important to continuously adapt and improve measurement strategies to keep up with changing market trends and customer needs.

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