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Measure space


Measure space


A measure space is a basic object of measure theory, a branch of mathematics that studies generalized notions of volumes. It contains an underlying set, the subsets of this set that are feasible for measuring (the σ-algebra) and the method that is used for measuring (the measure). One important example of a measure space is a probability space.

A measurable space consists of the first two components without a specific measure.

Definition

A measure space is a triple ( X , A , μ ) , {\displaystyle (X,{\mathcal {A}},\mu ),} where

  • X {\displaystyle X} is a set
  • A {\displaystyle {\mathcal {A}}} is a σ-algebra on the set X {\displaystyle X}
  • μ {\displaystyle \mu } is a measure on ( X , A ) {\displaystyle (X,{\mathcal {A}})}

In other words, a measure space consists of a measurable space ( X , A ) {\displaystyle (X,{\mathcal {A}})} together with a measure on it.

Example

Set X = { 0 , 1 } {\displaystyle X=\{0,1\}} . The σ {\textstyle \sigma } -algebra on finite sets such as the one above is usually the power set, which is the set of all subsets (of a given set) and is denoted by ( ) . {\textstyle \wp (\cdot ).} Sticking with this convention, we set

In this simple case, the power set can be written down explicitly:

As the measure, define μ {\textstyle \mu } by

so μ ( X ) = 1 {\textstyle \mu (X)=1} (by additivity of measures) and μ ( ) = 0 {\textstyle \mu (\varnothing )=0} (by definition of measures).

This leads to the measure space ( X , ( X ) , μ ) . {\textstyle (X,\wp (X),\mu ).} It is a probability space, since μ ( X ) = 1. {\textstyle \mu (X)=1.} The measure μ {\textstyle \mu } corresponds to the Bernoulli distribution with p = 1 2 , {\textstyle p={\frac {1}{2}},} which is for example used to model a fair coin flip.

Important classes of measure spaces

Most important classes of measure spaces are defined by the properties of their associated measures. This includes, in order of increasing generality:

  • Probability spaces, a measure space where the measure is a probability measure
  • Finite measure spaces, where the measure is a finite measure
  • σ {\displaystyle \sigma } -finite measure spaces, where the measure is a σ {\displaystyle \sigma } -finite measure

Another class of measure spaces are the complete measure spaces.

References


Text submitted to CC-BY-SA license. Source: Measure space by Wikipedia (Historical)


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