0
$\begingroup$

I am considering the following type of situation. Suppose we have a random probability measure, by which I mean a probability measure on a space of probability measures atop some Polish space $X$. In other words, consider $\Lambda \in \mathcal{P}(\mathcal{P}(X))$. Then, an empirical measure for $\Lambda$ has the form: $\frac{1}{N}\sum_{n=1}^{N} \delta_{\mu_i}$, where $\mu_i$ are i.i.d. random variables taking values in the space $\mathcal{P}(X)$ distributed according to $\Lambda$.

Now, given a specific outcome $\mu_i (\omega)$, we can again draw samples from $\mu_i (\omega)$ by considering some i.i.d. random variables $X_i$ distributed according to $\mu_i(\omega)$, and then form the empirical measure $$\hat{\mu}_i:=\frac{1}{M}\sum_{n=1}^{M} \delta_{X_i}$$. Then, it makes sense to think of the measure $$\frac{1}{N}\sum_{n=1}^{N} \delta_{\hat{\mu}_i}$$ as a "doubly empirical" measure for $\Lambda$, in the sense that we have drawn samples from $\Lambda$ and then drawn samples from those samples.

My question is: where in the literature has this object been considered? Does it already have a standard name in the literature? Googling has turned up nothing for me, nor does digging around in Kallenberg's Random Measures book.

$\endgroup$
2
  • 1
    $\begingroup$ Not an answer, but in statistics, the process of bootstrapping is as such: you take random variables, and redraw random variables in the outcomes of the first ones. $\endgroup$
    – Plop
    Commented Apr 3 at 5:58
  • $\begingroup$ A special case of this is considered in the nonparametric Bayes literature. They consider a particular probability distribution (Dirichlet prior) on the set of probability distributions and draw samples from a distribution drawn from it. For example, the book S. Ghosal and A. van der Vaart (2017) "Fundamentals of Nonparametric Bayesian Inference" p. 62 calls it the "sample from the Dirichlet process." $\endgroup$
    – user108
    Commented Apr 4 at 6:55

0

You must log in to answer this question.