Measure
(Positive) Measure | |
\mu:\mathcal{R}\rightarrow\bar{\mathbb{R} }_{\ge0} For a \sigma-ring, \mathcal{R} | |
Properties | |
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\forall\overbrace{(A_n)_{n=1}^\infty }^{\begin{array}{c}\text{pairwise}\\\text{disjoint}\end{array} }\subseteq\mathcal{R}[\mu\left(\bigudot_{n=1}^\infty A_n\right)=\sum^\infty_{n=1}\mu(A_n)] |
Contents
[hide]Definition
A (positive) measure, \mu is a set function from a \sigma-ring, \mathcal{R} , to the positive extended real values[Note 1], \bar{\mathbb{R} }_{\ge 0} [1][2][3]:
- \mu:\mathcal{R}\rightarrow\bar{\mathbb{R} }_{\ge0}
Such that:
- \forall(A_n)_{n=1}^\infty\subseteq\mathcal{R}\text{ pairwise disjoint }[\mu\left(\bigudot_{n=1}^\infty A_n\right)=\sum_{n=1}^\infty\mu(A_n)] (\mu is a countably additive set function)
- Recall that "pairwise disjoint" means \forall i,j\in\mathbb{N}[i\ne j\implies A_i\cap A_j=\emptyset]
Entirely in words a (positive) measure, \mu is:
- An extended real valued countably additive set function from a \sigma-ring, \mathcal{R} ; \mu:\mathcal{R}\rightarrow\bar{\mathbb{R} } .
Remember that every \sigma-algebra is a \sigma-ring, so this definition can be applied directly (and should be in the reader's mind) to \sigma-algebras
Terminology
For a set
We may say a set A\in\mathcal{R} (for a \sigma-ring \mathcal{R} ) is:
Term | Meaning | Example |
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Finite[1] | if \mu(A)<\infty |
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\sigma-finite[1] | if \exists(A_n)_{n=1}^\infty\subseteq\mathcal{R}\forall i\in\mathbb{N}[A\subseteq\bigcup_{n=1}^\infty A_n\wedge \mu(A_i)<\infty]
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Of a measure
We may say a measure, \mu is:
Term | Meaning | Example |
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Finite[1] | If every set in the \sigma-ring the measure is defined on is of finite measure
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\sigma-finite[1] | If every set in the \sigma-ring the measure is defined on is of \sigma-finite measure
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Complete | if \forall A\in\mathcal{R}\forall B\in\mathcal{P}(A)[(\mu(A)=0)\implies(B\in\mathcal{R})]
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Of a measure on a \sigma-algebra
If \mu:\mathcal{A}\rightarrow\bar{\mathbb{R} }_{\ge0} for a \sigma-algebra \mathcal{A} [Note 2] then we can define:
Term | Meaning | Example |
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Totally finite[1] | if the measure of X is finite
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Totally \sigma-finite[1] | if X is of \sigma-finite measure
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Immediate properties
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Claim: \mu(\emptyset)=0
Properties
TODO: Countable subadditivity and so forth
In common with a pre-measure
Related theorems
Examples
Trivial measures
Here \mathcal{R} is a \sigma-ring[Note 4]
- \mu:\mathcal{R}\rightarrow\{0,+\infty\} by \mu(A)=\left\{\begin{array}{lr}
0 & \text{if }A=\emptyset \\
+\infty & \text{otherwise}
\end{array}\right.
- Note that if we'd chosen a finite and non-zero value instead of +\infty it would not be a measure[Note 5], as take any non-empty A,B\in\mathcal{R} with A\cap B=\emptyset, for a measure we would have:
- \mu(A\cup B)=\mu(A)+\mu(B), which will yield v=2v\implies v=0 contradicting that \mu maps non-empty sets to finite non-zero values
- Note that if we'd chosen a finite and non-zero value instead of +\infty it would not be a measure[Note 5], as take any non-empty A,B\in\mathcal{R} with A\cap B=\emptyset, for a measure we would have:
- \mu:\mathcal{R}\rightarrow\{0\} by \mu:A\mapsto 0 is the trivial measure.
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See also
Notes
- Jump up ↑ Recall \bar{\mathbb{R} }_{\ge0} is \mathbb{R}_{\ge0}\cup\{+\infty\}
- Jump up ↑ Remember a sigma-algebra is just a sigma-ring containing the entire space.
- Jump up ↑ Sometimes stated as monotone (it is monotone in Measures, Integrals and Martingales in fact!)
- Jump up ↑ Remember every \sigma-algebra is a \sigma-ring, so \mathcal{R} could just as well be a \sigma-algebra
- Jump up ↑ Unless \mathcal{R} was a trivial \sigma-algebra consisting of the empty set and another set.
References
Note: Inline with the Measure theory terminology doctrine the references do not define a measure exactly as such, only an object that fits the place we have named measure. This sounds like a huge discrepancy but as is detailed on that page, it isn't.
- ↑ Jump up to: 1.0 1.1 1.2 1.3 1.4 1.5 1.6 Measure Theory - Paul R. Halmos
- Jump up ↑ Measures, Integrals and Martingales - René L. Schilling
- Jump up ↑ Measure Theory - Volume 1 - V. I. Bogachev
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