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Probability and Measure — Part 1
2025-02-07
2025-12-19

本篇是 Adam B Kashlak 老师的 Probability and Measure Theory 课程笔记 Part 1

Measure Theory#

Measures and σ\sigma-Fields#

σ\sigma-Field #

Question : What sets (subsets of Ω\Omega) am I allowed to measure?

Definition

For some set Ω\Omega, a σ\sigma-Field F\mathcal{F} is a collection of sets A∈ΩA\in \Omega s.t.

  1. ∅, Ω∈F\varnothing, ~\Omega \in \mathcal{F}
  2. If A∈FA\in \mathcal{F} then Ac∈FA^c \in \mathcal{F}
  3. F\mathcal{F} is closed under union: for a countable collection of sets {Ai}i=1∞\{A_i\}_{i=1}^\infty s.t. Ai∈FA_i \in \mathcal{F} for all i∈Ni\in \mathbb{N} then   ⋃i=1∞Ai∈F\displaystyle\bigcup_{i=1}^{\infty} A_i \in \mathcal{F}

    Equivalence  : F\mathcal{F} also contains countable intersections because  ⋂i=1∞Ai=⋃i=1∞Aic∈F~\displaystyle\bigcap_{i=1}^{\infty} A_i = \displaystyle\bigcup_{i=1}^{\infty} A_i^c\in \mathcal{F}

Measure#

Definition

A measure μ : F→R+\mu~:~\mathcal{F}\rightarrow\mathbb{R}_+ is a mapping from a σ\sigma-field F\mathcal{F} to the non-negative real numbers s.t.

  1. μ(∅)=0\mu(\varnothing) = 0
  2. For a pairwise disjoint collection {Ai}i=1∞\{A_i\}_{i=1}^\infty then μ(⋃i=1∞Ai)=∑i=1∞μ(Ai)\mu\left(\displaystyle\bigcup_{i=1}^{\infty} A_i\right) = \displaystyle\sum_{i=1}^{\infty} \mu(A_i)  (Countably Additivity)

Special Cases for a Measure Space (Ω,F,μ)(\Omega, \mathcal{F}, \mu):

  • If μ(Ω)=1\mu(\Omega) = 1 then we say that (Ω,F,μ)(\Omega, \mathcal{F}, \mu) is a Probability Measure
  • If μ(A)<∞\mu(A) < \infty for any AA then we say that μ\mu is a Finite Measure
  • If Ω=⋃i=1∞Ai\Omega=\displaystyle\bigcup_{i=1}^{\infty} A_i s.t. μ(Ai)<∞  ∀i \mu(A_i) < \infty ~~ \forall i~ then μ\mu is a σ\sigma-Finite Measure
    Example

    Ω=R \Omega=\mathbb{R}~,  μ([a,b])=b−a\mu([a,b])=b-a and R=⋃i=1∞[i−1,i]∪[−i,−i+1]\mathbb{R}= \displaystyle\bigcup_{i=1}^{\infty} [i-1,i]\displaystyle\cup[-i,-i+1] then μ\mu is a σ\sigma-Finite Measure

Power Set#

Definition

Power set P(Ω)\mathscr{P}(\Omega) or 2Ω2^\Omega is the set of all subsets of Ω\Omega

Semi-Ring of Sets#

Definition

A\mathcal{A}, a collection of subsets of Ω \Omega~, is called a Semi-Ring when

  1. ∅∈A\varnothing \in \mathcal{A}
  2. If A,B∈AA, B \in \mathcal{A} then A∩B∈AA\displaystyle\cap B \in \mathcal{A}
  3. If A,B∈AA, B \in \mathcal{A} then there exists a finite number of pariwise disjoint sets Ci∈AC_i \in \mathcal{A} for  i=1,⋯ ,n ~i=1,\cdots,n~ s.t. A∖B=⋃i=1nCiA\setminus B = \displaystyle\bigcup_{i=1}^{n} C_i
Example

A\mathcal{A} : all intervals (a,b](a,b] in R\mathbb{R} is a semi-ring

Ring of Sets#

Definition

A\mathcal{A}, a collection of subsets of Ω \Omega~, is called a Ring when

  1. ∅∈A\varnothing \in \mathcal{A}
  2. If A,B∈AA, B \in \mathcal{A} then A∖B∈AA\setminus B \in \mathcal{A}
  3. If A,B∈AA, B \in \mathcal{A} then A∪B∈A A\displaystyle\cup B\in \mathcal{A}~ (This implies finite unions are also in A\mathcal{A})

From the defintion, we know that the intersection of two sets is also in A\mathcal{A} because A∩B=A∖(A∖B)A\displaystyle\cap B = A\setminus (A\setminus B)

Example

All finite unions of half open intervals (a,b](a,b] in R\mathbb{R} is a ring

Field#

Definition

A\mathcal{A} is a Field if it is a Ring and Ω∈A\Omega \in \mathcal{A}

Equivalence

Since the whole set Ω\Omega is in A\mathcal{A}, then

  • the second condition of Ring is equivalent to A\mathcal{A} being closed under complimentation as A∖B=A∩AcA \setminus B = A \displaystyle\cap A^c and Ac=Ω∖AA^c = \Omega \setminus A
  • the third condition of Ring is equivalent to A\mathcal{A} being closed under finite unions as A∪B=(Ac∩Bc)cA\displaystyle\cup B = (A^c \displaystyle\cap B^c)^c

Note : Field + countable unions == σ\sigma-Field

Set Function#

Definition

A set function μ: A→R+\mu: ~\mathcal{A}\rightarrow \mathbb{R}^+ (not necessarily a measure) is a mapping from a set of functions A\mathcal{A} to R+\mathbb{R}^+. For A,B∈AA, B \in \mathcal{A}, we say that

  • μ\mu is monotone if A⊂BA\subset B implies μ(A)≤μ(B)\mu(A)\leq \mu(B)
  • μ\mu is additive if μ(A∪B)=μ(A)+μ(B)\mu(A\displaystyle\cup B) = \mu(A) + \mu(B) for A,BA, B disjoint
  • μ\mu is countably additive if μ(⋃i=1∞Ai)=∑i=1∞μ(Ai)\mu\left(\displaystyle\bigcup_{i=1}^{\infty} A_i\right) = \displaystyle\sum_{i=1}^{\infty} \mu(A_i) for {Ai}i=1∞\{A_i\}_{i=1}^\infty pairwise disjoint and ⋃i=1∞Ai∈A\displaystyle\bigcup_{i=1}^{\infty} A_i \in \mathcal{A}
  • μ\mu is countably sub-additive if μ(⋃i=1∞Ai)≤∑i=1∞μ(Ai)\mu\left(\displaystyle\bigcup_{i=1}^{\infty} A_i\right) \leq \displaystyle\sum_{i=1}^{\infty} \mu(A_i) for ⋃i=1∞Ai∈A\displaystyle\bigcup_{i=1}^{\infty} A_i \in \mathcal{A} (not nessarily pairwise disjoint)
  • μ\mu is a pre-measure if μ\mu is countably additive, μ(∅)=0\mu(\varnothing)=0 and A\mathcal{A} is a ring. For a pre-measure, it is also
    • monotone because for A⊂BA\subset B we have μ(B)=μ(A∪(B∖A))=μ(A)+μ(B∖A)≥μ(A)\mu(B)=\mu(A\displaystyle\cup (B\setminus A)) = \mu(A) + \mu(B\setminus A) \geq \mu(A)
    • sub-additive because for ⋃i=1∞Ai∈A\displaystyle\bigcup_{i=1}^{\infty} A_i \in \mathcal{A} let Bi=Ai∖(⋃j=1i−1Aj)B_i=A_i \setminus \left(\displaystyle\bigcup_{j=1}^{i-1} A_j\right) then BiB_i are pairwise disjoint and by monotonicity, μ(⋃i=1∞Ai)=μ(⋃i=1∞Bi)=∑i=1∞μ(Bi)≤∑i=1∞μ(Ai)\mu\left(\displaystyle\bigcup_{i=1}^{\infty} A_i\right) = \mu\left(\displaystyle\bigcup_{i=1}^{\infty} B_i\right) = \displaystyle\sum_{i=1}^{\infty} \mu(B_i) \leq \displaystyle\sum_{i=1}^{\infty} \mu(A_i)

Outter Measure#

Definition

For a pre-measure μ\mu on a ring A\mathcal{A}, the outter measure (Not necessarily a Measure) μ∗:M→R+\mu^* : \mathcal{M} \rightarrow \mathbb{R}^+ is defined as

μ∗(E)=inf⁡{∑i=1∞μ(Ai) : E⊂⋃i=1∞Ai, Ai∈A}\mu^*(E) = \inf \left\{ \displaystyle\sum_{i=1}^{\infty} \mu(A_i) ~:~ E\subset \displaystyle\bigcup_{i=1}^{\infty} A_i, ~A_i\in \mathcal{A} \right\}

for any E⊆ΩE\subseteq \Omega. This is equal to the smallest possible sum of the pre-measure over all finite or countable collections of AiA_i in A\mathcal{A} that cover EE.

Can we “Measure” (Outer Measure) any E⊂ΩE\subset \Omega ? Not necessarily

Denote M\mathcal{M} to be the collection of all μ∗\mu^* measurable sets where we say that B⊆ΩB\subseteq \Omega is μ∗\mu^* measureable when

μ∗(E∩B)+μ∗(E∩Bc)=μ∗(E)  ∀E⊆Ω\mu^*(E\displaystyle\cap B) + \mu^*(E\displaystyle\cap B^c) = \mu^*(E) ~~ \forall E\subseteq \Omega

Caratheodory Extension Theorem#

Caratheodory Extension Theorem

Let A\mathcal{A} be a ring on Ω\Omega and μ\mu be a pre-measure, then μ\mu extends to a measure on σ(A)\sigma(\mathcal{A}).

Note
  • σ(A)\sigma(\mathcal{A}) is the σ\sigma-field comes from extend A\mathcal{A} by including coutable unions and Ω\Omega itself.
  • The “corret” extension is the outter measure μ∗\mu^*.
Proof

Assume B⊂ΩB\subset \Omega and μ∗(B)<∞\mu^*(B)<\infty

  1. Prove stuff about μ∗\mu^*
    • μ∗(∅)=0\mu^*(\varnothing)=0 as μ\mu is a pre-measure

    • μ∗\mu^* is non-negative as μ\mu is non-negative

    • μ∗\mu^* is monotone (increasing)

      Let B1,B2⊂ΩB_1, B_2 \subset \Omega and B1⊂B2B_1\subset B_2 then for any Ai{A_i} s.t. B2⊆⋃iAiB_2 \subseteq \displaystyle\bigcup_i A_i. Then B1⊆⋃iAiB_1 \subseteq \displaystyle\bigcup_i A_i thus μ∗(B1)≤μ∗(B2)\mu^*(B_1)\leq \mu^*(B_2)

    • μ∗\mu^* is countably sub-additive

      For {Bi}i=1∞\{B_i\}_{i=1}^\infty and a given ϵ>0\epsilon > 0, let Bi⊆⋃iAijB_i\subseteq \displaystyle\bigcup_i A_{ij} for Aij∈AA_{ij}\in \mathcal{A} s.t.

      ∑iμ(Aij)≤μ∗(Bi)+ϵ⋅2−i\displaystyle\sum_i \mu(A_{ij}) \leq \mu^*(B_i) + \epsilon\cdot 2^{-i}

      This is possible because μ∗\mu^* is the infimum. As ⋃i=1∞Bi⊆⋃i,jAij\displaystyle\bigcup_{i=1}^\infty B_i \subseteq \displaystyle\bigcup_{i,j} A_{ij} and as μ∗\mu^* is monotone and μ\mu is sub-additive, then

      μ∗(⋃i=1∞Bi)≤μ(⋃i,jAij)≤∑i,jμ(Aij)≤∑iμ∗(Bi)+ϵ⋅2−i\begin{aligned} \mu^*\left(\displaystyle\bigcup_{i=1}^\infty B_i\right) &\leq \mu\left(\displaystyle\bigcup_{i,j} A_{ij}\right) \\ &\leq \displaystyle\sum_{i,j} \mu(A_{ij}) \\ &\leq \displaystyle\sum_i \mu^*(B_i) + \epsilon\cdot 2^{-i} \end{aligned}

      Take ϵ→0\epsilon\rightarrow 0 to get that μ∗\mu^* is countably sub-additive

  2. Check that μ\mu and μ∗\mu^* coincide for all A∈AA\in \mathcal{A}
    • For any A∈AA\in \mathcal{A} we have μ∗(A)≤μ(A)\mu^*(A) \leq \mu(A) because {A}\{A\} is a cover of AA and μ∗\mu^* is the infimum
    • For the reverse, if A⊂⋃iAiA\subset \displaystyle\bigcup_i A_i then by countable sub-additivity and monotonicity
    μ(A)≤∑iμ(A∩Ai)≤∑iμ(Ai)\mu(A) \leq \displaystyle\sum_i \mu(A\displaystyle\cap A_i) \leq \displaystyle\sum_i \mu(A_i) This implies that μ(A)≤μ∗(A)\mu(A)\leq \mu^*(A) because the right hand side is the cover of A.
    • Thus μ(A)=μ∗(A)  ∀A∈A\mu(A)=\mu^*(A) ~~ \forall A\in \mathcal{A}
  3. Check that the ring A⊂M\mathcal{A}\subset \mathcal{M} (all μ∗\mu^* measurable sets)
    • i.e. ∀A∈A\forall A \in \mathcal{A} we want to show that AA is μ∗\mu^*-measurable: μ∗(E∩A)+μ∗(E∩Ac)=μ∗(E)  ∀E⊆Ω\mu^*(E\displaystyle\cap A) + \mu^*(E\displaystyle\cap A^c) = \mu^*(E) ~~ \forall E\subseteq \Omega
    • Note μ∗(E∩A)+μ∗(E∩Ac)≥μ∗(E)\mu^*(E \displaystyle\cap A) + \mu^*(E\displaystyle\cap A^c) \geq \mu^*(E) as μ∗\mu^* is sub-additive.
    • Next, for some ϵ>0 \epsilon>0~, choose {Ai}\{A_i\} s.t. E⊂⋃iAiE\subset \displaystyle\bigcup_i A_i and ∑iμ(Ai)≤μ∗(E)+ϵ\displaystyle\sum_i \mu(A_i) \leq \mu^*(E) + \epsilon
    • Furthermore, E∩A⊂⋃i(A∩Ai)E\displaystyle\cap A\subset \displaystyle\bigcup_i(A\displaystyle\cap A_i) and E∩Ac⊂⋃i(Ac∩Ai)E\displaystyle\cap A^c \subset \displaystyle\bigcup_i(A^c\displaystyle\cap A_i) thus μ∗(E∩A)+μ∗(E∩Ac)≤∑iμ(A∩Ai)+∑iμ(Ac∩Ai)=∑iμ(Ai)≤μ∗(E)+ϵ\begin{aligned} \mu^*(E\displaystyle\cap A) + \mu^*(E\displaystyle\cap A^c) &\leq \displaystyle\sum_i \mu(A\displaystyle\cap A_i) + \displaystyle\sum_i \mu(A^c\displaystyle\cap A_i) \\ &= \displaystyle\sum_i \mu(A_i) \leq \mu^*(E) + \epsilon \end{aligned} and take ϵ→0\epsilon\rightarrow 0.
  4. Show that M\mathcal{M} is a σ\sigma-Field
    • ∅∈M\varnothing \in \mathcal{M} since ∅∈A\varnothing \in \mathcal{A}
    • Ω∈M\Omega \in \mathcal{M} since ∀E⊂Ω  μ∗(E∩Ω)+μ∗(E∩∅)=μ∗(E)\forall E\subset \Omega ~~ \mu^*(E\displaystyle\cap \Omega) + \mu^*(E\displaystyle\cap\varnothing)=\mu^*(E)
    • M\mathcal{M} is closed under coplimentation since μ∗(E∩Bc)+μ∗(E∩(Bc)c)=μ∗(E)\mu^*(E\displaystyle\cap B^c) + \mu^*(E\displaystyle\cap (B^c)^c) = \mu^*(E) which implies that Bc∈MB^c \in \mathcal{M}
    • M\mathcal{M} is closed under finite intersections since for B1,B2∈MB_1, B_2\in\mathcal{M} and any E⊂ΩE \subset \Omega μ∗(E)=μ∗(E∩B1)+μ∗(E∩B1c)=μ∗(E∩B1∩B2)+μ∗(E∩B1c∩B2)+μ∗(E∩B1∩B2c)+μ∗(E∩B1c∩B2c)≥μ∗(E∩B1∩B2)+μ∗({E∩B1c∩B2}∪{E∩B1∩B2c}∪{E∩B1c∩B2c})=μ∗(E∩{B1∩B2})+μ∗(E∩{B1∩B2}c)≥μ∗(E)     (sub-additivity)\begin{aligned} \mu^*(E)&=\mu^*(E\displaystyle\cap B_1) + \mu^*(E\displaystyle\cap B_1^c) \\ &= \mu^*(E\displaystyle\cap B_1\displaystyle\cap B_2) + \mu^*(E\displaystyle\cap B_1^c\displaystyle\cap B_2) + \mu^*(E\displaystyle\cap B_1\displaystyle\cap B_2^c) + \mu^*(E\displaystyle\cap B_1^c\displaystyle\cap B_2^c) \\ &\geq \mu^*(E\displaystyle\cap B_1\displaystyle\cap B_2) + \mu^*(\{E\displaystyle\cap B_1^c\displaystyle\cap B_2\}\displaystyle\cup\{E\displaystyle\cap B_1\displaystyle\cap B_2^c\}\displaystyle\cup \{E\displaystyle\cap B_1^c\displaystyle\cap B_2^c\}) \\ &=\mu^*(E\displaystyle\cap \{B_1\displaystyle\cap B_2\}) + \mu^*(E\displaystyle\cap \{B_1\displaystyle\cap B_2\}^c) \geq \mu^*(E) ~~~~~(\text{sub-additivity}) \end{aligned} thus B1∩B2∈MB_1\displaystyle\cap B_2 \in \mathcal{M}. Properties above show that M\mathcal{M} is a Field.
    • To get to a σ\sigma-Field, let {Bi}\{B_i\} in M\mathcal{M} be countable and parwise disjoint and ⋃iBi∈M\displaystyle\bigcup_i B_i \in \mathcal{M}. Let B=⋃i=1∞BiB = \displaystyle\bigcup_{i=1}^\infty B_i, then μ∗(E)=μ∗(E∩B1)+μ∗(E∩B1c)=μ∗(E∩B1)+μ∗(E∩B2)+μ∗(E∩B1c∩B2c)  ⋮=∑i=1nμ∗(E∩Bi)+μ∗(E∩{⋂i=1nBic})\begin{aligned} \mu^*(E) &= \mu^*(E\displaystyle\cap B_1) + \mu^*(E\displaystyle\cap B_1^c) \\ &= \mu^*(E\displaystyle\cap B_1) + \mu^*(E\displaystyle\cap B_2) + \mu^*(E\displaystyle\cap B_1^c\displaystyle\cap B_2^c) \\ &~~\vdots \\ &= \displaystyle\sum_{i=1}^n \mu^*(E\displaystyle\cap B_i) + \mu^*\left(E\displaystyle\cap\bigg\{\displaystyle\bigcap_{i=1}^n B_i^c\bigg\}\right) \\ \end{aligned} Then by monotonicity and sub-additivity and let n→∞n\rightarrow \infty, we get μ∗(E)=∑i=1∞μ∗(E∩Bi)+μ∗(E∩Bc)≥μ∗(E∩B)+μ∗(E∩Bc)≥μ∗(E)\begin{aligned} \mu^*(E) &= \displaystyle\sum_{i=1}^{\infty} \mu^*(E\displaystyle\cap B_i) + \mu^*(E\displaystyle\cap B^c) \\ &\geq \mu^*(E\displaystyle\cap B) + \mu^*(E\displaystyle\cap B^c) \\ &\geq \mu^*(E) \end{aligned} Thus M\mathcal{M} is closed under countable unions (M\mathcal{M} is a σ\sigma-Field!). Choose E=BE = B we have μ∗(E)=∑i=1∞μ∗(E∩Bi)\mu^*(E)=\displaystyle\sum_{i=1}^\infty \mu^*(E\displaystyle\cap B_i) which means μ∗\mu^* is countably additive.
  5. Conclusion: μ∗\mu^* is a set function 2Ω→R+2^\Omega\rightarrow \mathbb{R}^+ and it’s also a measure on M\mathcal{M}. Since A⊂M\mathcal{A}\subset \mathcal{M}, then σ(A)⊆M\sigma(\mathcal{A})\subseteq \mathcal{M}. Lastly, as μ∗\mu^* is a measure on M\mathcal{M}, it is also a measure on σ(A)\sigma(\mathcal{A}). □\square

π\pi-System and λ\lambda-System #

π\pi-system

A collection of sets A\mathcal{A} is a π\pi-system if

  • ∅∈A\varnothing \in \mathcal{A}
  • ∀A,B∈A\forall A, B \in \mathcal{A}, A∩B∈AA\displaystyle\cap B \in \mathcal{A}.
λ\lambda-system

A collection of sets L\mathcal{L} is a λ\lambda-system if

  • Ω∈L\Omega \in \mathcal{L}
  • If A,B∈LA, B \in \mathcal{L} and A⊂BA\subset B then B∖A∈LB\setminus A \in \mathcal{L}.
  • If {Ai}i=1∞\{A_i\}_{i=1}^\infty is a sequence of pairwise disjoint sets in L\mathcal{L} then ⋃i=1∞Ai∈L\displaystyle\bigcup_{i=1}^\infty A_i \in \mathcal{L}.

Note : a Field is a π\pi-system

Example

Let Ω={1,2,3,4}\Omega=\{1,2,3,4\} and L\mathcal{L} contains all subsets with an even number of elements. Then L\mathcal{L} is a λ\lambda-system but not a σ\sigma-Field since {1,2},{2,3}∈L\{1,2\}, \{2,3\}\in \mathcal{L} but {1,2}∪{2,3}={1,2,3}∉L\{1,2\}\displaystyle\cup\{2,3\}=\{1,2,3\}\notin \mathcal{L}

Dynkin π\pi-λ\lambda Theorem #

Dynkin π\pi-λ\lambda Theorem

Let A\mathcal{A} be a π\pi-system, L\mathcal{L} be a λ\lambda-system and A⊆L\mathcal{A}\subseteq \mathcal{L}. Then σ(A)⊆L\sigma(\mathcal{A})\subseteq \mathcal{L}.

Proof

Let L0\mathcal{L}_0 be the smallest λ\lambda-system such that A⊂L0\mathcal{A}\subset\mathcal{L}_0, then L0⊆L\mathcal{L}_0\subseteq\mathcal{L}. Our goal is to show that L0\mathcal{L}_0 is also a π\pi-system and a collection of sets that is both a π\pi-system and a λ\lambda-system is a σ\sigma-Field. Then we necessarily have that σ(A)⊆L0⊆L\sigma(\mathcal{A})\subseteq\mathcal{L}_0\subseteq\mathcal{L}.

We only need to show that L0\mathcal{L}_0 is closed under intersections.

Let L′={B∈L0:B∩A∈L0,∀A∈A}\mathcal{L}'=\{B\in\mathcal{L}_0 : B\displaystyle\cap A\in\mathcal{L}_0, \forall A\in\mathcal{A}\} then A⊂L′\mathcal{A}\subset\mathcal{L}' as A\mathcal{A} is a π\pi-system and let’s show that L′\mathcal{L}' is also a λ\lambda-system:

  • Ω∈L′\Omega\in\mathcal{L}' as A⊂L0\mathcal{A}\subset\mathcal{L}_0
  • If B1,B2∈L′B_1, B_2\in\mathcal{L}' s.t. B1⊂B2B_1\subset B_2 then for any A∈AA\in\mathcal{A} we have that B1∩A,B2∩A∈L0B_1\displaystyle\cap A, B_2\displaystyle\cap A\in\mathcal{L}_0. Thus (B2∩A)∖(B1∩A)=(B2∖B1)∩A∈L0(B_2\displaystyle\cap A)\setminus (B_1\displaystyle\cap A) = (B_2\setminus B_1)\displaystyle\cap A\in\mathcal{L}_0, which implies that B2∖B1∈L′B_2\setminus B_1\in\mathcal{L}'
  • If {Bi}i=1∞∈L′\{B_i\}_{i=1}^\infty\in\mathcal{L}' are pariwise disjoint, then for any A∈AA\in\mathcal{A}, A∩Bi∈L0A\displaystyle\cap B_i\in\mathcal{L}_0 thus ⋃i=1∞(A∩Bi)∈L0\displaystyle\bigcup_{i=1}^\infty (A\displaystyle\cap B_i)\in\mathcal{L}_0. This implies that A∩(⋃i=1∞Bi)=⋃i=1∞(A∩Bi)∈L0A\displaystyle\cap(\displaystyle\bigcup_{i=1}^\infty B_i)=\displaystyle\bigcup_{i=1}^\infty (A\displaystyle\cap B_i)\in\mathcal{L}_0. Hence, ⋃i=1∞Bi∈L′\displaystyle\bigcup_{i=1}^\infty B_i\in\mathcal{L}'.

By definition of L′\mathcal{L}', L′⊆L0\mathcal{L}'\subseteq \mathcal{L}_0 but L0\mathcal{L}_0 is the smallest. Thus L′=L0\mathcal{L}'=\mathcal{L}_0 and L0\mathcal{L}_0 is a λ\lambda-system. Therefore, L0\mathcal{L}_0 contains all intersections with elements of A\mathcal{A}.

Lastly, let L′′={B∈L0:B∩C∈L0 ∀ C∈L0}\mathcal{L}''=\{B\in\mathcal{L}_0 : B\displaystyle\cap C\in\mathcal{L}_0 ~\forall~ C\in\mathcal{L}_0\} since L0=L′\mathcal{L}_0=\mathcal{L}', A⊂L′′\mathcal{A}\subset \mathcal{L}''. Then do the same thing we did above to L′′\mathcal{L}'' to show that L′′\mathcal{L}'' is a λ\lambda-system and thus L′′=L0\mathcal{L}''=\mathcal{L}_0.

Therefore, L0\mathcal{L}_0 is closed under intersections and thus a σ\sigma-Field. This implies that σ(A)⊆L0⊆L\sigma(\mathcal{A})\subseteq\mathcal{L}_0\subseteq\mathcal{L}. □\square

Uniquessness of Extension Thereom#

Uniqueness of Extension

Let μ1,μ2\mu_1, \mu_2 be σ\sigma-Finite measures on σ(A)\sigma(\mathcal{A}) where A\mathcal{A} is a π\pi-system. Then, if ∀A∈A μ1(A)=μ2(A)\forall A\in\mathcal{A} ~\mu_1(A)=\mu_2(A) then μ1\mu_1 and μ2\mu_2 are equal on σ(A)\sigma(\mathcal{A}).

Proof (Finite Measures)

Assuming μ1(Ω)=μ2(Ω)<∞\mu_1(\Omega)=\mu_2(\Omega)<\infty

Let L={B⊂Ω:μ1(B)=μ2(B)}\mathcal{L}=\{B\subset\Omega : \mu_1(B)=\mu_2(B)\} and we only need to show that L\mathcal{L} is a λ\lambda-system because since A⊂L\mathcal{A}\subset\mathcal{L}, by Dynkin π\pi-λ\lambda Theorem, σ(A)⊂L\sigma(\mathcal{A})\subset\mathcal{L} which means μ1=μ2\mu_1=\mu_2 coincide on σ(A)\sigma(\mathcal{A}).

  • Ω∈L\Omega\in\mathcal{L}
  • If A,B∈LA, B\in\mathcal{L} with A⊂BA\subset B then μ1(B∖A)+μ1(A)=μ1(B)=μ2(B)=μ2(B∖A)+μ2(A)<∞\begin{aligned} \mu_1(B\setminus A) + \mu_1(A)&=\mu_1(B)\\ &=\mu_2(B)\\ &=\mu_2(B\setminus A) + \mu_2(A) < \infty \end{aligned} hence B∖A∈LB\setminus A\in\mathcal{L}
  • {Ai}i=1∞\{A_i\}_{i=1}^\infty are pairwise disjoint and Ai∈LA_i\in\mathcal{L} μ1(⋃i=1∞Ai)=∑i=1∞μ1(Ai)=∑i=1∞μ2(Ai)=μ2(⋃i=1∞Ai)<∞\begin{aligned} \mu_1(\displaystyle\bigcup_{i=1}^\infty A_i)=\displaystyle\sum_{i=1}^\infty \mu_1(A_i)&=\displaystyle\sum_{i=1}^\infty\mu_2(A_i)\\ &=\mu_2(\displaystyle\bigcup_{i=1}^\infty A_i) < \infty \end{aligned} hence ⋃i=1∞Ai∈L\displaystyle\bigcup_{i=1}^\infty A_i\in\mathcal{L}.

L\mathcal{L} is a λ\lambda-system! □\square

Proof (σ\sigma-Finite Measures)
  • For any A∈AA\in\mathcal{A} s.t. μ1(A)=μ2(A)<∞\mu_1(A)=\mu_2(A)<\infty, we define LA\mathcal{L}_A to be all B⊆ΩB\subseteq\Omega s.t. μ1(A∩B)=μ2(A∩B)\mu_1(A\displaystyle\cap B)=\mu_2(A\displaystyle\cap B).

    Proceeding as in the proof above, we can show that LA\mathcal{L}_A is a λ\lambda-system and thus σ(A)⊂LA ∀A∈A\sigma(A)\subset\mathcal{L}_A ~ \forall A\in\mathcal{A}.

  • By σ\sigma-Finiteness we decompose Ω=⋃i=1∞Ai\Omega=\displaystyle\bigcup_{i=1}^\infty A_i, Ai∈AA_i\in\mathcal{A} and μ1(Ai)=μ2(Ai)<∞\mu_1(A_i)=\mu_2(A_i) < \infty. For any B∈σ(A)B\in\sigma(\mathcal{A}) and any n∈Nn\in\mathbb{N}

    μ1(⋃i=1n(B∩Ai))=∑i=1nμ1(B∩Ai)−∑i<jμ1(B∩Ai∩Aj)+⋯\mu_1\left(\displaystyle\bigcup_{i=1}^n(B\displaystyle\cap A_i)\right)=\displaystyle\sum_{i=1}^n \mu_1(B\displaystyle\cap A_i)-\displaystyle\sum_{i < j}\mu_1(B\displaystyle\cap A_i \displaystyle\cap A_j) + \cdots

    here we use inclusion-exclusion formula. This also works for μ2\mu_2.

    Since A\mathcal{A} is a π\pi-system, Ai∩Aj∈AA_i\displaystyle\cap A_j\in\mathcal{A} as well as futher intersections, thus

    μ1(⋃i=1n(B∩Ai))=μ2(⋃i=1n(B∩Ai)) ∀n∈N\mu_1\left(\displaystyle\bigcup_{i=1}^n(B\displaystyle\cap A_i)\right)=\mu_2\left(\displaystyle\bigcup_{i=1}^n(B\displaystyle\cap A_i)\right) ~\forall n\in\mathbb{N}

    Let n→∞n\rightarrow\infty we get μ1(B)=μ2(B) ∀B∈σ(A)\mu_1(B)=\mu_2(B)~ \forall B\in\sigma(\mathcal{A}) □\square

Borel σ\sigma-Field#

Definition

B(R)=σ(open sets in R)\mathcal{B}(\mathbb{R})=\sigma(\text{open sets in }\mathbb{R})

Lebesgue Measure#

Definition

For any interval (a,b](a,b] in R\mathbb{R}, the Lebesgue measure is defined as λ((a,b])=b−a\lambda((a,b])=b-a.

Are there any A⊂P(Ω)A\subset \mathscr{P}(\Omega) s.t. AA is not λ\lambda-measurable? No

Example: Vitali Set
  • Let Ω=(0,1]\Omega=(0, 1], for x,y∈(0,1]x,y \in (0,1] define addition mod 11

    x+y={x+yif x+y≤1x+y−1if x+y>1x+y= \begin{cases} x+y & \text{if } x+y\leq 1 \\ x+y-1 & \text{if } x+y>1 \end{cases}

    Define L\mathcal{L} to contain all λ\lambda-measureable sets A⊆(0,1]A\subseteq (0,1] s.t. λ(A)=λ(A+x)\lambda(A)=\lambda(A+x) for any x∈(0,1]x \in (0,1], where A+x={x+y∈(0,1]:y∈A}A+x=\{x+y\in(0,1] : y \in A\} (shift AA by xx) then we claim that L\mathcal{L} is a λ\lambda-system.

    Since A\mathcal{A} is the set contains all intervals (a,b]⊆Ω(a, b]\subseteq \Omega, we have A⊂L\mathcal{A} \subset \mathcal{L} because λ((a,b])=b−a\lambda((a, b])=b-a and λ((a,b]+x)=λ((a+x,b+x])=b−a\lambda((a, b]+x)=\lambda((a+x, b+x])=b-a.

    By Dynkin π\pi-λ\lambda Theorem, σ(A)=B⊂L\sigma(\mathcal{A})=\mathcal{B}\subset\mathcal{L}

    i.e. Every Borel subset of (0,1](0, 1] is shift invariant w.r.t λ\lambda

  • Next, we say that x∼yx\sim y if x−y∈Qx-y\in\mathbb{Q} then we can decompose (0,1](0, 1] into disjoint Equivalence classes.

    Define H⊂(0,1]H\subset (0,1] s.t. HH contains one element from each equivalence class. (We can do this because of the Axiom of Choice) Then no two points in HH are equivalent. i.e. r1,r2∈Qr_1, r_2\in\mathbb{Q} then (H+r1)∩(H+r2)=∅(H+r_1)\displaystyle\cap(H+r_2)=\varnothing for r1≠r2r_1\neq r_2

    Thus (0,1]=⋃r∈Q(H+r)(0, 1]=\displaystyle\bigcup_{r\in\mathbb{Q}}(H+r) and by countably additivity

    1=λ((0,1])=∑r∈Qλ(H+r)1 = \lambda((0, 1]) = \displaystyle\sum_{r\in\mathbb{Q}}\lambda(H+r)

    since λ\lambda is traslation invariant, λ(H+r1)=λ(H+r2)=λ(H)\lambda(H+r_1)=\lambda(H+r_2)=\lambda(H).

    • If λ(H)=0\lambda(H)=0, then 1=∑r∈Qλ(H)=01=\displaystyle\sum_{r\in\mathbb{Q}}\lambda(H)=0.
    • If λ(H)>0\lambda(H)>0, then 1=∑r∈Qλ(H)=∞1=\displaystyle\sum_{r\in\mathbb{Q}}\lambda(H)=\infty

    which yields a contradiction. Thus HH is not λ\lambda-measurable and we call it Vitali Set.

  • Fun fact: Lebesgue Measure on R\mathbb{R} is the only translation invariant measure.

    • Same for Rn\mathbb{R}^n
    • There is no ∞\infty-dimensional Lebesgue Measure. i.e. No traslation invariant measure.

Product Measure#

Definition

For two Measure Spaces (X,X,μ)(\mathbb{X}, \mathcal{X}, \mu) and (Y,Y,ν)(\mathbb{Y}, \mathcal{Y}, \nu), define (X×Y,X×Y,π)(\mathbb{X}\times\mathbb{Y}, \mathcal{X}\times\mathcal{Y}, \pi) where π(A×B)=μ(A)ν(B)\pi(A\times B)=\mu(A)\nu(B) for A∈XA\in\mathcal{X} and B∈YB\in\mathcal{Y}.

Question : How are these related? B(X)×B(Y)\mathcal{B}(\mathbb{X})\times\mathcal{B}(\mathbb{Y}) and B(X×Y)\mathcal{B}(\mathbb{X}\times\mathbb{Y})

From Dudley 4.1.7 B(X)×B(Y)⊂B(X×Y)\mathcal{B}(\mathbb{X})\times\mathcal{B}(\mathbb{Y})\subset\mathcal{B}(\mathbb{X}\times\mathbb{Y}), but these two are “usually” equal to each other. e.g. X=Y=R\mathbb{X}=\mathbb{Y}=\mathbb{R}

Independence#

Independence for sets

For a countable collection of sets Ai,i∈IA_i, i\in \mathcal{I}, we say that the collection is independent if for all finite subsets J⊂IJ \subset I, we have

μ(⋂j∈JAj)=∏j∈Jμ(Aj)\mu\left(\displaystyle\bigcap_{j\in \mathcal{J}}A_j\right)=\displaystyle\prod_{j\in \mathcal{J}}\mu(A_j)
Independence for σ\sigma-Fields

For a countable collection of σ\sigma-Fields Fi⊂F,i∈IF_i \subset F, i \in \mathcal{I}, we say that this collection of σ\sigma-Fields is independent if any set of sets {Ai∈Fi:i∈I}\{A_i \in F_i : i \in \mathcal{I}\} is independent in the sense of the previous definition

Theorem

Let A1,A2⊂FA_1, A_2 \subset F be π\pi-systems. If μ(A1∩A2)=μ(A1)μ(A2)\mu(A_1 \displaystyle\cap A_2) = \mu(A_1)\mu(A_2) for any A1∈A1A_1 \in \mathcal{A}_1 and A2∈A2A_2 \in \mathcal{A}_2, then σ(A1)\sigma(A_1) and σ(A2)\sigma(A_2) are independent.

Proof

For a fixed A1∈A1A_1 \in \mathcal{A}_1, we can define two measures for B∈FB \in \mathcal{F} as

ν1(B)=μ(A1∩B)  and  ν2(B)=μ(A1)μ(B).\nu_1(B) = \mu(A_1 \displaystyle\cap B) ~~\text{and}~~ \nu_2(B) = \mu(A_1)\mu(B).

By assumption, ν1(A2)=ν2(A2)\nu_1(A_2) = \nu_2(A_2) for any A2∈A2A_2 \in \mathcal{A}_2. Hence, by Uniqueness of Extension Theorem, they must coincide on σ(A2)\sigma(A_2). Therefore, μ(A1∩B2)=μ(A1)μ(B2)\mu(A_1 \displaystyle\cap B_2) = \mu(A_1)\mu(B_2) for a fixed A1A_1 and any B2∈σ(A2)B_2 \in \sigma(A_2).

This argument can be repeated by fixing an element B2∈σ(A2)B_2 \in \sigma(A_2) to get that μ(B1∩B2)=μ(B1)μ(B2)\mu(B_1 \displaystyle\cap B_2) = \mu(B_1)\mu(B_2) for Bi∈σ(Ai),i=1,2B_i \in \sigma(A_i), i=1,2. □\square

Probability and Measure — Part 1
https://astronaut.github.io/posts/measure-theory-part1/
Author
关怀他人
Published at
2025-02-07
License
CC BY-NC-SA 4.0