In measure theory and probability, the monotone class theorem connects monotone classes and 𝜎-algebras. The theorem says that the smallest monotone class containing an algebra of sets
G
{\displaystyle G}
is precisely the smallest 𝜎-algebra containing
G
.
{\displaystyle G.}
It is used as a type of transfinite induction to prove many other theorems, such as Fubini's theorem.
Definition of a monotone class
A monotone class is a family (i.e. class)
M
{\displaystyle M}
of sets that is closed under countable monotone unions and also under countable monotone intersections. Explicitly, this means
M
{\displaystyle M}
has the following properties:
- if
A
1
,
A
2
,
…
∈
M
{\displaystyle A_{1},A_{2},\ldots \in M}
and A 1 ⊆ A 2 ⊆ ⋯ {\displaystyle A_{1}\subseteq A_{2}\subseteq \cdots }
then ⋃ i = 1 ∞ A i ∈ M , {\textstyle {\textstyle \bigcup \limits _{i=1}^{\infty }}A_{i}\in M,}
and
- if
B
1
,
B
2
,
…
∈
M
{\displaystyle B_{1},B_{2},\ldots \in M}
and B 1 ⊇ B 2 ⊇ ⋯ {\displaystyle B_{1}\supseteq B_{2}\supseteq \cdots }
then ⋂ i = 1 ∞ B i ∈ M . {\textstyle {\textstyle \bigcap \limits _{i=1}^{\infty }}B_{i}\in M.}
Monotone class theorem for sets
Monotone class theorem for sets—Let
G
{\displaystyle G}
be an algebra of sets and define
M
(
G
)
{\displaystyle M(G)}
to be the smallest monotone class containing
G
.
{\displaystyle G.}
Then
M
(
G
)
{\displaystyle M(G)}
is precisely the 𝜎-algebra generated by
G
{\displaystyle G}
; that is
σ
(
G
)
=
M
(
G
)
.
{\displaystyle \sigma (G)=M(G).}
Monotone class theorem for functions
Monotone class theorem for functions—Let
A
{\displaystyle {\mathcal {A}}}
be a π-system that contains
Ω
{\displaystyle \Omega \,}
and let
H
{\displaystyle {\mathcal {H}}}
be a collection of functions from
Ω
{\displaystyle \Omega }
to
R
{\displaystyle \mathbb {R} }
with the following properties:
- If
A
∈
A
{\displaystyle A\in {\mathcal {A}}}
then 1 A ∈ H {\displaystyle \mathbf {1} _{A}\in {\mathcal {H}}}
where 1 A {\displaystyle \mathbf {1} _{A}}
denotes the indicator function of A . {\displaystyle A.}
- If
f
,
g
∈
H
{\displaystyle f,g\in {\mathcal {H}}}
and c ∈ R {\displaystyle c\in \mathbb {R} }
then f + g {\displaystyle f+g}
and c f ∈ H . {\displaystyle cf\in {\mathcal {H}}.}
- If
f
n
∈
H
{\displaystyle f_{n}\in {\mathcal {H}}}
is a sequence of non-negative functions that increase to a bounded function f {\displaystyle f}
then f ∈ H . {\displaystyle f\in {\mathcal {H}}.}
Then
H
{\displaystyle {\mathcal {H}}}
contains all bounded functions that are measurable with respect to
σ
(
A
)
,
{\displaystyle \sigma ({\mathcal {A}}),}
which is the 𝜎-algebra generated by
A
.
{\displaystyle {\mathcal {A}}.}
Proof
The following argument originates in Rick Durrett's Probability: Theory and Examples.[1]
The assumption
Ω
∈
A
,
{\displaystyle \Omega \,\in {\mathcal {A}},}
(2), and (3) imply that
G
=
{
A
:
1
A
∈
H
}
{\displaystyle {\mathcal {G}}=\left\{A:\mathbf {1} _{A}\in {\mathcal {H}}\right\}}
is a 𝜆-system.
By (1) and the π−𝜆 theorem,
σ
(
A
)
⊆
G
.
{\displaystyle \sigma ({\mathcal {A}})\subseteq {\mathcal {G}}.}
Statement (2) implies that
H
{\displaystyle {\mathcal {H}}}
contains all simple functions, and then (3) implies that
H
{\displaystyle {\mathcal {H}}}
contains all bounded functions measurable with respect to
σ
(
A
)
.
{\displaystyle \sigma ({\mathcal {A}}).}
Results and applications
As a corollary, if
G
{\displaystyle G}
is a ring of sets, then the smallest monotone class containing it coincides with the 𝜎-ring of
G
.
{\displaystyle G.}
By invoking this theorem, one can use monotone classes to help verify that a certain collection of subsets is a 𝜎-algebra.
The monotone class theorem for functions can be a powerful tool that allows statements about particularly simple classes of functions to be generalized to arbitrary bounded and measurable functions.
See also
- Dynkin system – Family closed under complements and countable disjoint unions
- π-𝜆 theorem – Family closed under complements and countable disjoint unionsPages displaying short descriptions of redirect targets
- π-system – Family of sets closed under intersection
- σ-algebra – Algebraic structure of set algebra
Citations
- Durrett, Rick (2010). Probability: Theory and Examples (4th ed.). Cambridge University Press. p. 276. ISBN 978-0521765398.
References
- Durrett, Richard (2019). Probability: Theory and Examples (PDF). Cambridge Series in Statistical and Probabilistic Mathematics. Vol. 49 (5th ed.). Cambridge New York, NY: Cambridge University Press. ISBN 978-1-108-47368-2. OCLC 1100115281. Retrieved November 5, 2020.