Combined sample spaces .

  • Thread starter mmzaj
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  • #1
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Dear all

I've just begun studying measure theory , and i cant help it but to think of it in terms of probability theory , i don't know if that is right or wring . any way , i have this naive question :

consider the following : we have n sample spaces [tex]\Omega_{}i[/tex], each with a distribution P[tex]_{}i[/tex] ( i=1,...n) , if we combine (union) the sample spaces to form a new sample space whose distribution is unknown , is there a way to extract the distribution of the new sample space from the previously know distributions ??
 

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  • #2
EnumaElish
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The simplest case is to assume disjoint sample spaces. In that case, the probability of obtaining element x from the k'th space, x(k), will be P{x(k)} = P{x|k}P{k} = Pk{x}P{k}, where P{k} is the probability of obtaining the k'th space within the set of all spaces, or the measure of the k'th space in the union.

In general:

[tex]P\{x\} = \sum_{k=1}^N P\{x|k\}P\{k\}[/tex]

where N is the number of spaces.

This is related to the axiom of independence [from] irrelevant alternatives in decision theory.
 
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what about the general case ?
 
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EnumaElish
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See the portion of my post that begins with "In general."
 

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