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world:de-finetti [2026/02/07 10:32] rdouc [Proof] |
world:de-finetti [2026/02/07 12:44] (current) rdouc |
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| - | on{{page>:defs}} | + | {{page>:defs}} |
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| <WRAP center round tip 80%> | <WRAP center round tip 80%> | ||
| **De Finetti's Theorem:** | **De Finetti's Theorem:** | ||
| - | Let $(X_i)_{i\in\mathbb{N}}$ be a family of **exchangeable random elements** taking balues on a measurable space $(\mathsf{X},\mathcal{X})$. Then, there exists a $\sigma$-field $\mathcal{G}_\infty$ such that, **conditionally on $\mathcal{G}_\infty$**, the random variables $(X_i)_{i\in\mathbb{N}}$ are **independent and identically distributed (i.i.d.)**. | + | Let $(X_i)_{i\in\mathbb{N}}$ be a family of **exchangeable random elements** taking values on a measurable space $(\mathsf{X},\mathcal{X})$. Then, there exists a $\sigma$-field $\mathcal{G}_\infty$ such that, **conditionally on $\mathcal{G}_\infty$**, the random variables $(X_i)_{i\in\mathbb{N}}$ are **independent and identically distributed (i.i.d.)**. |
| </WRAP> | </WRAP> | ||
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| =\prod_{\ell=1}^k\mathbb{E}[f_\ell(X_1)\mid\mathcal{G}_\infty]. | =\prod_{\ell=1}^k\mathbb{E}[f_\ell(X_1)\mid\mathcal{G}_\infty]. | ||
| $$ | $$ | ||
| - | * Thus, conditionally on $\mathcal{G}_\infty$, $(X_i)$ are independent. | + | * Thus, conditionally on $\mathcal{G}_\infty$, $(X_i)$ are independent. $\blacksquare$ |
| <WRAP center round todo 80%> | <WRAP center round todo 80%> | ||
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| \left\{ \mathbb{E}\big[\mathbf{1}_{\{X_1 \le x\}} \mid \mathcal{G}_\infty \big] : x \in \mathbb{Q} \right\}. | \left\{ \mathbb{E}\big[\mathbf{1}_{\{X_1 \le x\}} \mid \mathcal{G}_\infty \big] : x \in \mathbb{Q} \right\}. | ||
| \] | \] | ||
| - | It follows that there exists a random variable $S$ such that, conditional on $S$, the sequence $(X_i)$ is independent and identically distributed. <span>■</span> | + | It follows that there exists a random variable $S$ such that, conditional on $S$, the sequence $(X_i)$ is independent and identically distributed. |
| </WRAP> | </WRAP> | ||
| - | ==== Comments: convergence of Empirical Averages for i.i.d. Random Variables ==== | + | ==== Comments: Another proof of the Law of Large Numbers for i.i.d. Random Variables ==== |
| The previous approach allows to prove the strong law of large numbers (for a proof of the LLN using only the dominated convergence theorem, [[world:lln| click here]]) | The previous approach allows to prove the strong law of large numbers (for a proof of the LLN using only the dominated convergence theorem, [[world:lln| click here]]) | ||