Section 11.5

Product Measures: The Tonelli and Fubini Theorems

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Problem 11.41

Let (X,A,μ)=(Y,B,ν)=(N,2N,c)(X, \mathcal{A}, \mu ) = (Y, \mathcal{B}, \nu ) = \left(\mathbb {N}, 2^{\mathbb {N}}, c\right). Show that the product measure is the counting measure. State the Fubini and Tonelli Theorems explicitly for this case.

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Problem 11.42

Show that the smallest σ\sigma-algebra that contains all products of Lebesgue measurable subsets of R\mathbb {R} is the Borel σ\sigma-algebra B(R2)\mathcal{B}\left(\mathbb {R}^{2}\right).

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Problem 11.43

Assume (X,A,μ)(X, \mathcal{A}, \mu ) and (Y,B,ν)(Y, \mathcal{B}, \nu ) are complete, h:X→[0,∞]h: X \rightarrow [0, \infty ] and g:Y→[0,∞]g: Y \rightarrow [0, \infty ] are nonnegative and integrable, and define k(x,y)=h(x)⋅g(y)k(x, y) = h(x) \cdot g(y). Show that kk is a (μ×ν)(\mu \times \nu )-integrable and

∫X×Ykd(μ×ν)=∫Xhdμ⋅∫Ygdν \int _{X \times Y} k d(\mu \times \nu ) = \int _{X} h d \mu \cdot \int _{Y} g d \nu
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Problem 11.44

Define f:N×N→Rf: \mathbb {N} \times \mathbb {N} \rightarrow \mathbb {R} by setting

f(m,n)={2−2−mif m=n−2+2−mif m=n+10otherwise f(m, n) = \begin{cases} 2-2^{-m} & \text{if } m = n \\ -2+2^{-m} & \text{if } m = n+1 \\ 0 & \text{otherwise} \end{cases}

Show that ff is measurable with respect to the product measure space. Also show that

∫N[∫Nf(m,n)dc(m)]dc(n)≠∫N[∫Nf(m,n)dc(n)]dc(m) \int _{\mathbb {N}}\left[\int _{\mathbb {N}} f(m, n) d c(m)\right] d c(n) \neq \int _{\mathbb {N}}\left[\int _{\mathbb {N}} f(m, n) d c(n)\right] d c(m)

Is this a contradiction either of Fubini's Theorem or Tonelli's Theorem?

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Problem 11.45

Let (X,A,μ)(X, \mathcal{A}, \mu ) be a complete measure space. Consider N×X\mathbb {N} \times X with the product measure c×μc \times \mu.

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(i)

Show that a subset EE of N×X\mathbb {N} \times X is measurable with respect to the product measure space if and only if for each k,Ek={x∈X∣(k,x)∈E}k, E_{k} = \left\{ x \in X \mid (k, x) \in E\right\} is measurable with respect to μ\mu.

(ii)

Show that a function f:N×X→Rf: \mathbb {N} \times X \rightarrow \mathbb {R} is measurable with respect to the product measure space if and only if for each k,f(k,⋅):X→Rk, f(k, \cdot ): X \rightarrow \mathbb {R} is measurable with respect to μ\mu.

(iii)

Show that a function f:N×X→Rf: \mathbb {N} \times X \rightarrow \mathbb {R} is integrable over N×X\mathbb {N} \times X with respect to c×μc \times \mu if and only if for each k,f(k,⋅):X→Rk, f(k, \cdot ): X \rightarrow \mathbb {R} is integrable over XX with respect to μ\mu and

∑k=1∞∫X∣f(k,x)∣dμ(x)<∞ \sum _{k = 1}^{\infty } \int _{X}\left|f(k, x)\right| d \mu (x) < \infty
(iv)

Show that if the function f:N×X→Rf: \mathbb {N} \times X \rightarrow \mathbb {R} is integrable over N×X\mathbb {N} \times X with respect to c×μc \times \mu, then

∫N×Xfd(c×μ)=∑k=1∞∫Xf(k,x)dμ(x)<∞ \int _{\mathbb {N} \times X} f d(c \times \mu ) = \sum _{k = 1}^{\infty } \int _{X} f(k, x) d \mu (x) < \infty
Problem 11.46

Prove that the conclusion of Tonelli's Theorem holds if one of the spaces is the space (N,2N,c\mathbb {N}, 2^{\mathbb {N}}, c) and the other space is a complete measure space that need not be σ\sigma-finite.

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Problem 11.47

If {(Xk,Ak,μk)}k=1n\left\{ \left(X_{k}, \mathcal{A}_{k}, \mu_{k}\right)\right\}_{k = 1}^{n} is a finite collection of measure spaces, define the product measure μ1×⋯×μn\mu_{1} \times \cdots \times \mu_{n} on the space X1×⋯×XnX_{1} \times \cdots \times X_{n} by starting with the semi-ring of rectangles of the form R=A1×⋯×AnR = A_{1} \times \cdots \times A_{n}, define μ(R)=∏μk(Ak)\mu (R) = \prod \mu_{k}\left(A_{k}\right), show that μ\mu is a premeasure and define the product measure to be the Carathéodory extension of μ\mu. Show that if (X1×⋯×Xp)×(Xp+1×⋯×Xn)\left(X_{1} \times \cdots \times X_{p}\right) \times \left(X_{p+1} \times \cdots \times X_{n}\right) is identified with (X1×⋯×XnX_{1} \times \cdots \times X_{n}), then

(μ1×⋯×μp)×(μp+1×⋯×μn)=μ1×⋯×μn. \left(\mu _{1} \times \cdots \times \mu _{p}\right) \times \left(\mu _{p+1} \times \cdots \times \mu _{n}\right) = \mu _{1} \times \cdots \times \mu _{n} .
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Problem 11.48

A measure space (X,M,μX, \mathcal{M}, \mu) such that μ(X)=1\mu (X) = 1 is called a probability measure space. Let {(Xλ,Aλ,μλ)}λ∈Λ\left\{ \left(X_{\lambda }, \mathcal{A}_{\lambda }, \mu_{\lambda }\right)\right\}_{\lambda \in \Lambda } be a collection of probability measure spaces parametrized by the set Λ\Lambda. Show that it is possible to define a probability measure

μ=∏λ∈Λμλ \mu = \prod _{\lambda \in \Lambda } \mu _{\lambda }

on a suitable σ\sigma-algebra on the Cartesian product ∏λ∈ΛXλ\prod_{\lambda \in \Lambda } X_{\lambda } so that

μ(A)=∏λ∈Λμλ(Aλ) \mu (A) = \prod _{\lambda \in \Lambda } \mu _{\lambda }\left(A_{\lambda }\right)

when A=∏λ∈ΛAλA = \prod_{\lambda \in \Lambda } A_{\lambda }. (Note that μ(A)\mu (A) can only be non-zero if all but a countable number of the AλA_{\lambda } have μ(Aλ)=1\mu \left(A_{\lambda }\right) = 1.)

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