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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.
Depends on
Used by
- Birkhoff strong law for iid coordinate shifts Corollary
- Countably many independent copies of a prescribed law exist Corollary
- Summable untruncated variances are not necessary Counterexample
- A canonical random walk from product increments Example
- A Lindeberg array with no identically distributed row Example
- A nonidentical Bernoulli weak law Example
- Almost sure frequency of heads Example
- An i.i.d. sequence with a prescribed law Example
- Independent but non-identically distributed coordinates Example
- The infinite fair-coin-toss space Example
- The three series impose separate conditions Example
- Independent Brownian motion straightens a Poisson clock Lemma
- Disjoint streams of independent fair bits produce independent uniform variables Theorem
- Rejection sampling is uniform, almost surely terminating, and has expected linear bit cost Theorem
Dependency tree · two levels
15 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Kajino, Probability Theory, Proposition 3.67 (standard reference, not scraped)