View source for Measurable map

'''Note: ''' Sometimes called a ''measurable [[Function|fuction]]''<ref name="PAS">Probability and Stochastics - Erhan Cinlar</ref>
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==Definition==
Let {{M|(X,\mathcal{A})}} and {{M|(X',\mathcal{A}')}} be [[Measurable space|measurable spaces]] then a map:
* <math>T:X\rightarrow X'</math> 
is called '''<math>\mathcal{A}/\mathcal{A}'</math>-measurable'''<ref name="MIM">Measures, Integrals and Martingales - Rene Schilling</ref>, or '''<math>\mathcal{A}-\mathcal{A}'</math>-measurable'''<ref name="PTACC">Probability Theory - A Comprehensive Course - Second Edition - Achim Klenke</ref>, or '''Measurable relative to {{M|\mathcal{A} }} and {{M|\mathcal{A}'}}'''<ref name="PAS"/> if:
* <math>T^{-1}(A')\in\mathcal{A},\ \forall A'\in\mathcal{A}'</math>

'''See also:'''
* (Theorem) [[Conditions for a map to be a measurable map]]
* (Theorem) [[A map from two sigma-algebras, A and B, is measurable if and only if for some generator of B (call it G) we have the inverse image of S is in A for every S in G|A map, {{M|f:(A,\mathcal{A})\rightarrow(F,\mathcal{F})}}, is {{M|\mathcal{A}/\mathcal{F} }} measurable ''iff'' for some generator {{M|\mathcal{F}_0}} of {{M|\mathcal{F} }} we have {{M|\forall S\in\mathcal{F}_0[f^{-1}(S)\in\mathcal{A}]}}]]

==Notation==
I like the ''{{M|\mathcal{A}/\mathcal{B} }}-measurable'' notation because it reads nicely for composition. As [[Composition of measurable maps is measurable|a composition of measurable maps is measurable]]<ref name="PAS"/> we see something like, if:
* {{M|f:(A,\mathcal{A})\rightarrow(B,\mathcal{B})}} is measurable (same as saying: {{M|f:A\rightarrow B}} is {{M|\mathcal{A}/\mathcal{B} }}-measurable) and
* {{M|g:(B,\mathcal{B})\rightarrow(C,\mathcal{C})}} is measurable 
then:
* {{M|g\circ f:(A,\mathcal{A})\rightarrow(C,\mathcal{C})}} is measurable.

In effect:
* {{M|\mathcal{A}/\mathcal{B} }}-measurable followed by {{M|\mathcal{B}/\mathcal{C} }} measurable {{M|1==}} {{M|\mathcal{A}/\mathcal{C} }}-measurable
==Terminology==
* {{M|\mathcal{A} }}-measurable is short hand for {{M|\mathcal{A}/\mathcal{B}(\overline{\mathbb{R} })}}-measurable - where {{M|\mathcal{B} }} denotes the [[Borel sigma-algebra|Borel {{sigma|algebra}}]] and {{M|1=\overline{\mathbb{R} }=\mathbb{R}\cup\{-\infty,+\infty\} }}<ref name="MIM"/><ref name="PAS"/>
* A ''Borel function'' is a mapping from the [[Borel sigma-algebra|Borel {{sigma|algebra}}]] of a [[Topological space|topological space]], {{M|(X,\mathcal{J})}}, then the {{M|\mathcal{B}((X,\mathcal{J}))}}-measurable functions are called ''Borel functions''<ref name="PAS"/> 
==(OLD) Notation==
{{Todo|Confirm this - it could just be me getting ahead of myself}}
A given a [[Measure space|measure space]] (a measurable space equipped with a measure) {{M|(X,\mathcal{A},\mu)}} with a measurable map on the following mean the same thing:
* <math>T:(X,\mathcal{A},\mu)\rightarrow(X',\mathcal{A}',\bar{\mu})</math> (if {{M|(X',\mathcal{A}')}} is also equipped with a measure)
* <math>T:(X,\mathcal{A},\mu)\rightarrow(X',\mathcal{A}')</math>
* <math>T:(X,\mathcal{A})\rightarrow(X',\mathcal{A}')</math>

We would write <math>T:(X,\mathcal{A},\mu)\rightarrow(X',\mathcal{A}')</math> simply to remind ourselves of the measure we are using, it is not important to the concept of the measurable map.

As usual, the function is on the first thing in the bracket. (see [[Function|function]] for more details)

==Motivation==
From the topic of [[Random variable|random variables]] - which a special case of measurable maps (where the domain can be equipped with a probability measure, a measure where {{M|X}} has measure 1).


Consider: <math>X:(\Omega,\mathcal{A},\mathbb{P})\rightarrow(V,\mathcal{U})</math>, we know that given a {{M|U\in\mathcal{U} }} that {{M|T^{-1}\in\mathcal{A} }} which means we can measure it using {{M|\mathbb{P} }}, which is something we'd want to do.

{{Begin Example}}
Example using sum of two die RV
{{Begin Example Body}}
Take <math>\Omega=\{(a,b)|a,b\in\mathbb{N}\, a,b\in[1,6]\}</math> and <math>\mathcal{A}=\sigma(\Omega)=\mathcal{P}(\Omega)</math>, define <math>\mathbb{P}:\mathcal{P}(\Omega)\rightarrow[0,1]\subset\mathbb{R}</math> by <math>\mathbb{P}(A)\mapsto \frac{1}{36}|A|</math>

Take the random variable <math>X:(\Omega,\mathcal{P}(\Omega),\mathbb{P})\rightarrow(\{2,\cdots,12\},\mathcal{P}(\{2,\cdots,12\}))</math> which assigns each {{M|(a,b)}} to {{M|a+b}} - the sum of the scores.

It is clear for example that only <math>\{(1,2),(2,1)\}</math> thus the probability of getting 3 as the sum is 2 out of 36 or {{M|\frac{1}{18} }}
{{End Example Body}}
{{End Example}}

==See also==
* [[Random variable]]
* [[Probability space]]
* [[Measurable space]]
* [[Conditions for a map to be a measurable map]]
==References==
<references/>

{{Definition|Measure Theory}}