Notation question for probability measures on product spaces

In summary, there is a unique probability measure ##\mu## on (A\times B, \mathcal A\otimes\mathcal B) which can be defined as ##\mu(\hat A\times \hat B) = \int_{\hat A} q(\hat B|\cdot)\text{ d}p## for every ##\hat A\in\mathcal A, \hat B\in\mathcal B##. It is denoted as ##\mu_{p,q}## in the current context, but no standard name or notation has been found for it.
  • #1
economicsnerd
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Let [itex](A,\mathcal A), (B,\mathcal B)[/itex] be measurable spaces. Let [itex]p[/itex] be a probability measure on [itex](A,\mathcal A)[/itex], and let [itex]q:A\to\mathcal P(B,\mathcal B)[/itex] be a measurable function which takes each [itex]a\in A[/itex] to some probability measure [itex]q(\cdot|a)[/itex] on [itex](B,\mathcal B).[/itex] Then there is a unique probability measure [itex]\mu[/itex] on [itex](A\times B, \mathcal A\otimes\mathcal B)[/itex] which has [tex]\mu(\hat A\times \hat B) = \int_{\hat A} q(\hat B|\cdot)\text{ d}p[/tex] for every [itex]\hat A\in\mathcal A, \hat B\in\mathcal B.[/itex]

The question: Is there a typical thing to call [itex]\mu[/itex]? Does it have a name, in terms of [itex]p[/itex] and [itex]q[/itex]? How about notation? [itex]pq[/itex]? [itex]p\otimes q[/itex] (which would be misleading)? [itex]q\circ p[/itex]? [itex]q^p[/itex]? I looked around and couldn't find anything consistent.
 
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  • #2
I'm sorry you are not generating any responses at the moment. Is there any additional information you can share with us? Any new findings?
 
  • #3
No such luck. In the thing I'm writing, I just named it ##\mu_{p,q}## and fully defined it, since I couldn't find a standard name for it. I figured I'll fix it later if I stumble on a good name elsewhere.
 

1. What is the notation used for probability measures on product spaces?

The notation used for probability measures on product spaces is typically denoted by P(A), where A is an event or set of events. It represents the probability of the event or set of events occurring in the product space.

2. How is the probability of a product space calculated?

The probability of a product space is calculated by multiplying the individual probabilities of the events or sets of events within the product space. This can be represented mathematically as P(A) = P(A1) * P(A2) * ... * P(An), where A1, A2, ..., An are the individual events or sets of events in the product space.

3. What is the significance of using product spaces in probability measures?

Product spaces are used in probability measures to represent the likelihood of multiple events occurring simultaneously. They allow for the calculation of joint probabilities, which can provide a more comprehensive understanding of the relationships between different events.

4. Can the probability of a product space be greater than 1?

No, the probability of a product space cannot be greater than 1. This would violate the fundamental rule of probability, which states that the probability of any event must be between 0 and 1, inclusive.

5. How is the notation for probability measures on product spaces different from traditional probability notation?

The main difference between notation for probability measures on product spaces and traditional probability notation is the use of subscripts and multiplication symbols. Product spaces often use subscripts to represent different events or sets of events within the product space, and multiplication symbols are used to denote the calculation of joint probabilities.

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