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Infinite Product Measures and Kolmogorov Extension
1 · Prerequisites
- Compactness
- Compactness in Metric Spaces
- Complete Metrizability, Čech-Completeness, and Baire Category
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Foundations of the Real Numbers for Analysis
- Independence Borel Cantelli and Zero One Laws
- limsup, liminf, and Subsequential Limits
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- Outer Measure and the Caratheodory Extension Theorem
- Probability Spaces Random Variables and Expectation
- Product Measures and the Fubini Tonelli Theorems
- Relations, Functions, and Quotients
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sigma Algebras and Borel Sets
- Suprema and Infima
- The Lebesgue Integral and the Convergence Theorems
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
2 · Summary
This page separates countable products of arbitrary probability spaces from arbitrary-index extension of consistent laws on standard-Borel coordinates. Both constructions live on the generated cylinder sigma-algebra.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Coordinate maps, finite-coordinate cylinders, and the cylinder -algebra
Definition
For measurable spaces , put . For finite , let be restriction to (the singleton empty product when ). On , write for the th coordinate map and define
For this is the two-set sigma-algebra on the singleton. If is any enumeration, coordinate relabelling identifies this sigma-algebra with the recursively defined finite product sigma-algebra of The product sigma-algebra and its finite iterates: both are generated by the same coordinate inverse images. Thus the notation is independent of the enumeration.
A finite-coordinate cylinder is for . The cylinder sigma-algebra is
This is the product sigma-algebra on the arbitrary product; the empty-support cylinder is either or .
Finite-coordinate cylinders form a -system
Statement
The finite-coordinate cylinders in form a pi-system.
Facts & Assumptions
Given: Two finite-coordinate cylinders and .
Their supports are finite, and their bases are measurable in the respective finite product sigma-algebras.
Proof
Put and let be the coordinate projections from . Then is measurable in .
Directly from restriction of coordinates, , a finite-coordinate cylinder. The family is nonempty because it contains , so it is a pi-system.
Finite-coordinate cylinder sets form an algebra
Statement
The family of all finite-coordinate cylinders in is an algebra of subsets of .
Facts & Assumptions
Given: Cylinders and .
A finite product sigma-algebra is closed under complements, inverse images under coordinate projections, and finite unions.
Proof
The empty-support cylinders give . Also .
For , pull both bases to ; their union is measurable and its inverse image is . Thus has the three algebra operations.
A consistent family of finite-dimensional distributions
Definition
Let be measurable spaces. A family , indexed by all finite subsets of , is a consistent family of finite-dimensional distributions when each is a probability measure on , with the finite unordered product sigma-algebra of Coordinate maps, finite-coordinate cylinders, and the cylinder -algebra, and for every pair of finite sets the pushforward of under the restriction equals ; equivalently, for every . The restriction is measurable since inverse images of coordinate generators are coordinate generators. The empty support carries the unique probability measure on the singleton empty product.
Reordering means choosing a different enumeration of the same finite set . If is an enumeration, its displayed ordered law is the pushforward of under . For another enumeration , the coordinate permutation pushes this ordered law to the one displayed using . This is automatic from these definitions and does not require equal laws on different subsets of , or invariance under permutations of a fixed ordered product. In particular, consistency is data about every finite joint law, not merely the one-coordinate marginals.
Consistent finite-dimensional laws define a well-defined finitely additive cylinder law
Statement
Suppose the product is nonempty. For a consistent family , the formula is well-defined on and is finitely additive.
Facts & Assumptions
Given: A nonempty product , a consistent family , and a finite disjoint cylinder decomposition.
If , consistency says .
Finite-coordinate cylinders form an algebra. (Finite-coordinate cylinder sets form an algebra)
Proof
Fix . If , pull both sets to . Their lifted bases are equal: otherwise a point of their symmetric difference, combined with the coordinates of outside , would distinguish the cylinders. Hence consistency gives .
For disjoint cylinders with , pull all bases to . They are disjoint measurable sets, so finite additivity of yields . The union is in the cylinder algebra by [F2].
The countable-product cylinder premeasure is countably additive
Statement
Assume countable choice and dependent choice. For a countable sequence of probability spaces and its finite-product cylinder law , is a premeasure on the cylinder algebra.
Facts & Assumptions
Given: Countable choice, dependent choice, a countable sequence of probability spaces, its cylinder algebra, and the finitely additive law .
The finite-coordinate product law is a probability measure and has the rectangle formula. (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)
For product-measurable in two sigma-finite factors, each section is measurable, its section-measure function is measurable, and the product mass is the integral of that function. (For sigma-finite measures, the section-measure functions are measurable, The product measure of two sigma-finite measure spaces)
A decreasing sequence of measurable sets with finite first measure has measure converging to that of its intersection. (Continuity from above when one set has finite measure)
Countable choice supplies a point of the product of the nonempty coordinate spaces. (The Axiom of Countable Choice ())
Under countable choice, a countable union of finite coordinate supports is countable. (Countable unions of at most countable sets, assuming )
Dependent choice licenses a recursively constructed sequence when the admissible next coordinate depends on the prefix already chosen. (The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain)
Proof
Every coordinate space is nonempty because it carries a probability measure. By [F4], the coordinate product is therefore nonempty, so the finitely additive cylinder law is well-defined. Let be cylinders and suppose that for every . By [F5], enumerate the countable union of their finite supports. After enlarging supports, take to be determined by the first active coordinates, with nondecreasing. Recursively regarding each finite product as a two-factor product, [F2] expresses each cylinder mass as the integral of its measurable next-coordinate section-mass function.
The finite-stage section argument recursively maintains the following invariant after coordinates have been chosen: every remaining -section has tail-cylinder mass at least . For a prefix with this invariant, let be the measurable set of possible next coordinates whose further section has mass at least . The decrease with . The section formula and the bound by give the next-coordinate measure of at least ; [F3] therefore makes nonempty. Every choice from this intersection extends the prefix and preserves the invariant.
By [F6], make the recursively compatible selections from step 2.1. For each , once the first active coordinates have been selected, they lie in the finite base of because its remaining section has positive mass. Fill any inactive coordinates with the product point supplied by [F4]. The resulting point lies in every , contradicting . Thus .
Finite additivity plus continuity at the empty set gives countable additivity whenever a disjoint union remains a cylinder: apply it to the decreasing remainders. Hence is a premeasure.
Assuming countable and dependent choice, countable products of arbitrary probability spaces
Statement
Assume countable choice and dependent choice. For probability spaces there is a unique probability measure on such that, for every finite , its -coordinate marginal is .
Facts & Assumptions
Given: Countable choice, dependent choice, and a sequence of probability spaces.
Under the two stated choice principles, the cylinder law with the displayed finite product values is a premeasure. (The countable-product cylinder premeasure is countably additive)
Assuming countable choice, a premeasure extends to a measure on the sigma-algebra it generates. (Assuming countable choice, a premeasure extends through its induced outer measure)
A lambda-system containing a pi-system contains the sigma-algebra generated by that pi-system. (Dynkin's pi-lambda theorem)
Proof
Define . The finite product marginals are consistent, so [F1] applies.
By [F2], extends to a measure on the generated cylinder sigma-algebra. Since the empty cylinder is and has value , is a probability measure.
Let be another probability measure with the stated marginals. The family is a lambda-system: it contains the whole space because both measures have mass one, is closed under relative complements of nested members, and is closed under increasing countable unions by continuity from below. The two measures agree on every cylinder, and cylinders are a pi-system by Finite-coordinate cylinders form a -system, so [F3] gives . Hence .
Coordinate random elements of a countable product are independent
Statement
Under the measure of Assuming countable and dependent choice, countable products of arbitrary probability spaces, the coordinate maps have laws and are independent.
Facts & Assumptions
Given: The canonical countable product probability space and finitely many distinct indices .
The product measure has every prescribed finite product marginal. (Assuming countable and dependent choice, countable products of arbitrary probability spaces)
Independence of random elements means the finite intersection formula for their measurable inverse images. (Independent random elements)
Proof
For and the distinct indices fixed above, [F1] gives ; taking one coordinate gives the asserted law.
The right side is , which is exactly [F2]. Since the finite family was arbitrary, all coordinates are independent.
Countably many independent copies of a prescribed law exist
Statement
Assume countable choice and dependent choice. Every probability measure on is the common law of a countable independent family of -valued random elements.
Facts & Assumptions
Given: Countable choice, dependent choice, and a measurable probability space .
Under countable choice and dependent choice, the canonical countable product probability measure exists. (Assuming countable and dependent choice, countable products of arbitrary probability spaces)
Its canonical coordinates have their prescribed laws and are independent. (Coordinate random elements of a countable product are independent)
Proof
Apply [F1] with and for every , and write for its coordinate maps.
By [F2], every has law and every finite subfamily is independent; this is the required independent-copy sequence.
Stochastic processes and their finite-dimensional distributions
Definition
For , let be a random element. The family is a stochastic process. For an ordered tuple of distinct times , its finite-dimensional distribution is the pushforward law of on . These laws, including their coordinate order, form a consistent family under deletion and permutation of times.
Process law, modification, and indistinguishability
Definition
Two processes with the same index set and corresponding target spaces have the same process law if all corresponding finite-dimensional laws agree; their source probability spaces need not be the same. Suppose in addition that and are defined on one common probability space , take values in the same measurable space at each , and is measurable for each . Then is a modification (or version) of when for every fixed . They are indistinguishable when the event is measurable and has probability one. The latter has one exceptional null event; the former may have a different null event at every time.
Standard Borel spaces
Definition
A measurable space is standard Borel if there are a Polish space and a bijection such that exactly when is Borel in . Thus the measurable structure is part of the datum; no particular compatible Polish topology on is selected.
Finite products of standard Borel spaces are standard Borel
Statement
Every finite product of standard Borel spaces, with its finite product sigma-algebra, is standard Borel.
Facts & Assumptions
Given: Standard-Borel spaces for .
Each is measurably isomorphic to the Borel space of a Polish space. (Standard Borel spaces)
Proof
Choose Polish presentations from [F1]. The product map is a bijection from to .
A finite product of Polish spaces is Polish, and inverse images under of its Borel rectangles are exactly the finite product measurable rectangles. Therefore transports its Borel sigma-algebra to , proving the claim.
Assuming countable choice, Borel probability measures on Polish spaces are inner regular
Statement
Assume countable choice. If is Polish and is a Borel probability measure on , then for every Borel and there is a compact with .
Facts & Assumptions
Given: A complete separable metric presentation , a Borel probability , and .
A Polish space has a complete compatible metric and a countable dense set. (Polish spaces are separable completely metrizable spaces)
Measures are continuous from below and countably subadditive. (Continuity from below for measures, Finite and countable subadditivity of measures)
A closed totally bounded subset of a complete metric space is compact. (A subspace of a complete metric space is complete iff it is closed, and a complete subspace of any metric space is closed, A complete, totally bounded metric space is compact, proved from countable choice used exactly once)
A lambda-system containing a pi-system contains the sigma-algebra it generates. (Dynkin's pi-lambda theorem)
Proof
The empty is immediate, so suppose and enumerate a countable dense set as . For each , continuity from below chooses a finite union of -balls centered at the with . Countable choice makes these choices simultaneously.
The set is closed. Countable subadditivity gives . For every scale, one of the finite closed-ball covers from step 1.1 covers ; choosing one point of from each nonempty member of that finite cover and doubling the radius gives a finite net with centres in . Hence is totally bounded and [F3] makes it compact.
Every open contains a compact losing less than : for use ; otherwise intersect with the increasing closed sets . Their union is , so [F2] gives one with the required loss.
Let be the Borel sets which, for every , have compact with open and . Step 3.1 puts every open set in . The tight compact set from step 2.1 shows that complements remain in : from , use and bound the loss by .
For pairwise disjoint , continuity from below makes the measure of the tail of arbitrarily small. A finite union of compact inner approximants handles that tail, while the union of the open outer approximants has loss bounded by the summable errors. Thus is a lambda-system. Open sets are a pi-system generating the Borel sigma-algebra, so [F4] gives . The compact inner approximant for proves the statement.
Assuming the Axiom of Choice, Kolmogorov extension for arbitrary families of standard Borel coordinate spaces
Statement
Assume the Axiom of Choice. For any set , standard-Borel coordinate spaces , and consistent finite-dimensional laws , there is a unique probability measure on whose -coordinate marginal is for each finite .
Facts & Assumptions
Given: AC, standard-Borel coordinates, and a consistent family .
Consistency gives a well-defined finitely additive cylinder law. (Consistent finite-dimensional laws define a well-defined finitely additive cylinder law)
After one Polish presentation is fixed on every coordinate, each finite product has the corresponding product Polish presentation; coordinate restrictions between such products are continuous. Its probability measures admit compact inner approximations, and compact metric spaces are sequentially compact. (Standard Borel spaces, Finite products of standard Borel spaces are standard Borel, Assuming countable choice, Borel probability measures on Polish spaces are inner regular, In any metric space compactness implies countable compactness and limit point compactness, and each of countable compactness and limit point compactness implies sequential compactness; every implication here is proved without a choice principle)
AC supplies both countable choice and values in every nonempty family of otherwise unconstrained coordinate spaces. (The Axiom of Choice, The Axiom of Countable Choice ())
Assuming countable choice, a premeasure extends to its generated sigma-algebra. (Assuming countable choice, a premeasure extends through its induced outer measure)
Proof
By AC, choose once and for all, for every , a Polish presentation witnessing that is standard Borel. Pull the topology and a complete compatible metric of back to . The finite product topologies now used below come from these same coordinate presentations, so every restriction map between them is continuous.
Let be cylinders and suppose their cylinder masses stayed above . Enumerate the countable union of their finite supports. For each , choose a nested finite support that contains both the original support of and the first active coordinates, and view as a cylinder over . In the product presentation fixed in step 1.1, inner-regularly replace its -base by a compact base, losing less than . Finite intersections of the lifted compact cylinders then have positive cylinder mass.
For each , choose a point in the intersection of the first lifted compact cylinders from step 2.1. For fixed , all points with have their -coordinates in the compact th base. Sequential compactness successively supplies a subsequence converging on , a further subsequence converging on , and so on; take the diagonal subsequence. Because every restriction is continuous by step 1.1, the successive limits restrict to the earlier limits. They therefore define one point on the union of the active coordinates. Each compact base is closed, so this point lies in every lifted compact cylinder.
Use AC to fill the inactive coordinates. The resulting point lies in every , a contradiction. Hence the cylinder law is continuous at the empty set and is a premeasure.
By [F4] it extends to and has total mass one. Two such extensions agree on all cylinders; these are a pi-system, so Dynkin's pi-lambda theorem gives uniqueness on , and nowhere larger.
Arbitrary products of standard Borel probability spaces
Statement
Assume AC. For standard-Borel probability spaces there is a unique probability measure on whose finite-coordinate marginals are the finite product measures .
Facts & Assumptions
Given: AC and a family of standard-Borel probability spaces.
Finite product measures have the rectangle formula and are probability measures. (For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique)
Kolmogorov extension applies to every consistent finite-dimensional family on standard-Borel coordinates. (Assuming the Axiom of Choice, Kolmogorov extension for arbitrary families of standard Borel coordinate spaces)
Proof
For finite , define . The rectangle formula shows that projecting to gives , so the family is consistent.
Apply [F2] to . Its conclusion is exactly the stated measure and its cylinder-sigma uniqueness; it does not assert a measure on .
The canonical coordinate process realizes consistent finite-dimensional laws
Statement
Under the extension measure of Assuming the Axiom of Choice, Kolmogorov extension for arbitrary families of standard Borel coordinate spaces, is a process whose finite-dimensional distributions are the prescribed .
Facts & Assumptions
Given: The extension measure on the cylinder space and its coordinate maps.
The extension has marginal under every finite-coordinate projection. (Assuming the Axiom of Choice, Kolmogorov extension for arbitrary families of standard Borel coordinate spaces)
Proof
Each coordinate map is measurable because inverse images of its measurable sets are one-coordinate cylinders. Thus is a process.
For finite , , so its pushforward law is by [F1]. This is precisely the finite-dimensional-law convention.
Finite-dimensional distributions determine a process law on the cylinder sigma-algebra
Statement
If two probability measures on have equal finite-dimensional marginals, then they are equal.
Facts & Assumptions
Given: Probability measures on with equal finite-dimensional marginals.
Finite-coordinate cylinders form a pi-system generating . (Finite-coordinate cylinders form a -system)
A lambda-system containing a pi-system contains the sigma-algebra it generates. (Dynkin's pi-lambda theorem)
Proof
On , complements and disjoint countable unions preserve equality because both measures are probabilities. Thus is a lambda-system.
Equal finite-dimensional marginals put every cylinder in . By [F1] and [F2], , hence .
Assuming countable choice, cylinder-measurable events depend on only countably many coordinates
Statement
Assume countable choice. For every there is a countable such that implies .
Facts & Assumptions
Given: Countable choice, the arbitrary product , and its cylinder sigma-algebra.
The cylinder sigma-algebra is generated by finite-coordinate cylinders. (Coordinate maps, finite-coordinate cylinders, and the cylinder -algebra)
Under countable choice, a countable union of countable sets is countable. (Countable unions of at most countable sets, assuming )
Proof
Let be the events determined by some countable coordinate set. Complements preserve the same support. For a countable family in , countable choice selects one countable support for each event, and [F2] makes their union countable; that union determines the union of the events. Thus is a sigma-algebra.
Every finite-coordinate cylinder belongs to , using its finite support. By generated-sigma minimality and [F1], .
The cylinder sigma-algebra need not be the full path-space power set
Assuming countable choice, for uncountable every -event is determined by countably many coordinates (Assuming countable choice, cylinder-measurable events depend on only countably many coordinates). Thus a subset that is not determined by any countable coordinate set is not in ; such subsets occur, for example, in uncountable Bernoulli path spaces. Consequently the extension theorems in general construct measures only on , not on every subset of path space and not for every set-defined path functional. If every coordinate space is a singleton, by contrast, the path space is a singleton and is its full power set. The companion counterexample makes the proper-inclusion boundary concrete.
State-space and index-set boundaries of the two extension routes
Under countable choice and dependent choice, the countable theorem Assuming countable and dependent choice, countable products of arbitrary probability spaces covers arbitrary measurable coordinate spaces but only product finite marginals. The arbitrary-index theorem Assuming the Axiom of Choice, Kolmogorov extension for arbitrary families of standard Borel coordinate spaces covers general consistent finite-dimensional laws, but requires standard-Borel coordinates and AC in the compact-product route. Recursive kernel constructions require extra conditional-probability data and belong to the later Markov-kernel page.
5 · Examples, counterexamples and false statements
None yet.
Sources
- Kajino, Probability Theory, Definition 3.64
- Biskup, MATH 275D notes, Lemma 2.6
- Kajino, Probability Theory, proof of Theorem 3.65
- Biskup, MATH 275D notes, Definition 2.2
- Kajino, Probability Theory, Theorem 3.65
- Kajino, Probability Theory, Proposition 3.67
- Durrett, Probability: Theory and Examples, Section 2.1.4
- Biskup, MATH 275D notes, Definition 2.1
- Biskup, MATH 275D notes, Section 2.3
- Biskup, MATH 275D notes, Definition 2.3
- Biskup, MATH 275D notes, Lemma 2.8
- Biskup, MATH 275D notes, Lemma 2.7
- Biskup, MATH 275D notes, Theorem 2.4
- Shalizi, Building Processes, Theorem 29
- Biskup, MATH 275D notes, Corollary 2.13
- Shalizi, Building Processes, proof of Theorem 29