[]\fnmRaghavendra \surTripathi
[]\orgdivDepartment of Mathematics, \orgnameUniversity of Washington, \citySeattle, \postcode, \stateWashington, \countryUSA
Two-color exchangeability does not imply exchangeability
Abstract
We provide simple examples of two-color exchangeable sequences that are not exchangeable. This answers a question of Bladt and Shaiderman [1, Question 2.6] for finite two-color exchangeable sequences.
1 Introduction
A finite or infinite sequence of random variables taking values in a Polish space is exchangeable if
for every and every permutation on . Exchangeability is possibly one of the most widely studied topic in probability since the work of de Finetti’s in 1930. Given a finite or infinite sequence of random variables , one can associate a sequence of random empirical measures as . The following theorem stated in [2] characterizes exchangeable sequences in terms of associated sequence of random empirical.
Theorem 1 (Kallenberg).
A sequence is exchangeable if and only if the associated sequence of empirical measures forms a reverse martingale (with respect to the filtration ).
Although the above result is correct, the proof presented in [2] was not completely rigorous. The first complete proof of the above result was presented only very recently in [1]. The authors in [1] introduce a notion of two-color exchangeability which seems interesting in its own right. We present the definition below [1, Definition 2.4] for completeness. We also refer the reader to [1, Section 2.2] for an interesting connection of two-color exchangeability with Strassen’s marginal problem [3, 4].
Definition 1 (Two-color exchangeability).
A finite or infinite sequence of random variables taking values in a Polish space is said to be two-coloring exchangeable if is a binary exchangeable sequence for every measurable function .
It is easy to see that if a sequence is exchangeable then it is also two-color exchangeable. The author in [1, Question 2.6] ask if the converse is true or not?
The purpose of this short note is to answer the above question in negative for finite sequences. In particular, for each , we construct a sequence of random variables taking values in such that is two-color exchangeable but not exchangeable. For pedagogical reasons, we first give such an example for case in Section 2 and then in Section 3 we construct the example for general .
2 Case
Let where are random variables taking values in . We now specify the distribution of . Suppose,
Note that is not exchangeable since
However, we will show that is two-color exchangeable. To this end, we need to check that is exchangeable for every . We begin by noting that there are a total of such function. For or , we trivially have that is exchangeable.
For , define by where if and otherwise. And, define . It is easy to check that these are all (non-trivial) binary functions on . It is also easy to see that is exchangeable if and only if is exchangeable. Therefore, it suffices to check that is exchangeable for . This is done by simple calculation that we furnish below for completeness.
In the following, we write for the probability mass function of for simplicity. Note that
Since , it follows that is exchangeable. Similar calculations hold for and as well. This completes the proof.
2.1 A word about the above counterexample
It might be instructive to say a few words about how we arrived at the above counterexample. To this end, we started with the simplest case of a sequence of two random variables taking values in a discrete set with three elements. For simplicity, we take the range of the random variables to be .
Let . Since can take only distinct values, the probability mass function of is completely determined by an element where is the unit simplex . Let denote the probability mass function of and denote
Any arbitrary choice of non-negative real numbers and such that yields a unique probability mass function and hence uniquely determines a random vector . The following fact is straightforward.
Fact 1.
Let be as above. Then, is exchangeable if and only if for .
On the other hand, doing a calculation similar to the one done in the above subsection yields the following.
Fact 2.
is two-color exchangeable if and only if
Now it is easy to construct examples of two-color exchangeable sequences of length that are not exchangeable.
3 Case
Throughout this section, we fix . We will construct such that each takes values in such that is two-color exchangeable but not exchangeable. Note that takes values in . However, for simplicity we will only consider the random vectors that take values in where
In particular, if then contains exactly two distinct symbols from and one of those symbols occurs with multiplicity . We, therefore, partition , by the symbol occurring exactly once, as , where is defined for each as
For later use we make a convention to denote the elements of . Let . Then, there are exactly two elements such that . We arrange these elements in lexicographic order and call them and respectively. Note that .
Let be a random vector taking values in and let denote the law of . Notice that can be identified with a vector where is the -dimensional unit simplex. In other words, any collection of non-negative real numbers such that determines a unique random vector taking values in .
We now record the following immediate fact.
Fact 3.
Let be the law of a random vector taking values in . Then, is exchangeable if and only if and are independent of for each (that is for all and each and similarly for ).
We now investigate the conditions for to be two-color exchangeable. To do this, let be any non-constant function and let be a random vector taking value in . Then, the random vector takes values in the set where
We further partition as where for . Let be a random vector taking values in and let denote the law of . Since each is an orbit under permutations of some binary string of length , it follows that is exchangeable if and only if is constant on for each . Note that and therefore any is trivially constant on .
As argued in Section 2, is two-color exchangeable if and only if to be exchangeable for each with . Let denote the law of where . Checking the condition that is constant on for yields the following six conditions:
-
1.
is constant on if and only if is independent of
-
2.
is constant on if and only if is independent of
-
3.
is constant on if and only if is independent of
-
4.
is constant on if and only if is independent of
-
5.
is constant on if and only if is independent of
-
6.
is constant on if and only if is independent of
3.1 A concrete example
It is clear from the above discussion that there are two-color exchangeable sequences that are not exchangeable. For completeness, we specify a particular distribution on that is two-color exchangeable but not exchangeable.
To define , it is enough to specify and for and . To this end, we set
The constant is normalizing constant to make a probability measure. Note that is not exchangeable because depends on , in particular, . However, notice that for all and for each . Thus, is exchangeable for each . In particular, is two-color exchangeable.
4 Conclusion and further direction
Constructing similar examples of infinite sequence that is two-color exchangeable but not exchangeable may be more delicate. We leave this investigation for future.
The notion of two-color exchangeability, even if it is not equivalent to exchangeablility, seems an interesting concept to study. Exchangeable sequences arise naturally in sampling without replacement. It would be interesting to find similar processes where two-color exchangeability arises naturally.
References
- \bibcommenthead
- Bladt and Shaiderman [2022] Bladt, M., Shaiderman, D.: Characterisation of exchangeable sequences through empirical distributions. To appear in Electronic Communications in Probability (2022) https://doi.org/10.48550/arXiv.1903.07861
- Kallenberg [2005] Kallenberg, O.: Probabilistic Symmetries and Invariance Principles vol. 9. Springer, New-York (2005)
- Strassen [1965] Strassen, V.: The existence of probability measures with given marginals. The Annals of Mathematical Statistics 36(2), 423–439 (1965)
- Edwards [1978] Edwards, D.A.: On the existence of probability measures with given marginals. In: Annales de L’institut Fourier, vol. 28, pp. 53–78 (1978)