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For a while, I have been strunggling to find why Levy's continuity Theorem would imply that:

$P_{n} \xrightarrow{\text{distribution}} P\iff \phi_{n}(t)\xrightarrow{n \to \infty}\phi(t)\; $

since Levy's Continuity Theorem is concerned with weak convergence rather than convergence in distribution. I thus attempted to find an equivalence between convergence in distribution and weak convergence. This leads me to the Portmanteau Lemma which shows many equivalent notions of weak convergence. So I am to attempt the following equivalence in the case of the measure being on $\mathbb R$:

$$ P_{n}\xrightarrow{\text{weakly}}P \iff P_{n}\xrightarrow{\text{distribution}}P$$

For "$\Rightarrow$" consider the equivalent notion of "weak convergence" from the Portmanteau Lemma, namely:

$P_{n}(A)\xrightarrow{n \to \infty} P(A)$ for any $P$-continuity set $A$.

Now let $x$ be a continuity point of $F$ in $\mathbb R$, then the set $(-\infty,x]$ is a continuity set under $P$ and hence: $F_{n}(x)=P_{n}((-\infty,x])\xrightarrow{n \to \infty} P((-\infty,x])=F(x)$ thus $F_{n}\xrightarrow{ \text{distribution}} F$.

I do not know what equivalent definition of weak convergence to prove for "$\Leftarrow$" direction. Continuity sets could take vastly different forms to $(-\infty,x]$ , thus I do not think I could use it. Any help would be greatly appreciated.

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  • $\begingroup$ What is your question? Do you want to prove that $P_n(A)$ for any P-continuity set A iff $F_n(x) \to F(x)$ for all continuity points of $F$? Or do you want to prove that one of them is equivalent to convergence of characteristic functions? Anyway these facts can be found in any good book about probability theory. Do you have any troubles with proofs from these books, and if yes, then what are they? $\endgroup$ Commented Dec 31, 2020 at 16:26

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I believe from your question that you take as definition of convergence in distribution that $\lim_n F_n(x) = F(x)$ where $x$ is a continuity point of $F$. Hence, I will show that this condition implies $$\liminf_n P_n(G) \geq P(G)$$ for all non-empty open subsets $G$ (you already proved the converse). The latter condition is equivalent with weak convergence, by the Portmanteau lemma.

Fix such a non-empty open subset $G$. For any $x \in G$, the fact that $G$ is open allows us to select $\epsilon_x > 0$ with $]x-2\epsilon_x, x + 2\epsilon_2[\subseteq G$. Then $G= \bigcup_{x \in G} ]x-\epsilon_x, x + \epsilon_x[$. By a theorem of Lindelöf (every open cover has a countable subcover), we can select a sequence $(x_n)_n\subseteq G$ with $G = \bigcup_{n=1}^\infty ]x-\epsilon_{x_n}, x + \epsilon_{x_n}[$ and by our construction also $$]x_n-2\epsilon_{x_n}, x_n + 2 \epsilon_{x_n}[\subseteq G.$$ Since $F$ is monotone, the set $D(F)$ of points of discontinuity is at most countable. Hence, for any $n \geq 1$, we can find $a_n, b_n$ continuity points with $$x_n - 2 \epsilon_{x_n} < a_n < x_n- \epsilon_{x_n}< x_n + \epsilon_{x_n} < b_n < x_n + 2 \epsilon_{x_n}.$$ It follows that $G = \bigcup_{n=1}^\infty]a_n, b_n]$ where $a_n < b_n$ are continuity points for all $n \geq 1$. Put $$\mathcal{P}:= \{]a,b]: a < b, a,b \notin D(F)\}\cup\{\emptyset\}.$$ Then $\mathcal{P}$ is closed under finite intersections. If $C = ]a,b] \in \mathcal{P}$, then \begin{align}\lim_n P_n(C) &= \lim_n \{P_n(]-\infty, b])- P_n(]-\infty, a])\}\\ &=\lim_n {F_n(b)- F_n(a)}\\ &= F(b)-F(a) = P(C).\end{align} If $C_1, \dots, C_m \in \mathcal{P}$, then by inclusion-exclusion principle also $$\lim_n P_n\left(\bigcup_{i=1}^m C_i\right) = P \left(\bigcup_{i=1}^m C_i\right).$$ Hence, for all $m \geq 1$, $$\liminf_n P_n(G) \geq \liminf_n P_n\left(\bigcup_{i=1}^m ]a_i, b_i]\right) = P\left(\bigcup_{i=1}^m ]a_i, b_i]\right).$$ But $\bigcup_{i=1}^m ]a_i, b_i[ \nearrow G$, so by continuity of measure we obtain $$\liminf_n P_n(G) \geq P(G).$$

Feel free to ask for clarification if something is not clear to you!

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