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Hoi, if $\mu_1,\mu_2,\cdots$ are probability measures on $(\mathbb{R}, \mathcal{B}),$ with distribution functions $F_1,F_2,\cdots $

I want to show: If for all $x\in C_F$ (all $x$ where $F$ is continuous), we have $F_n(x)\to F(x)$ then we have weak convergence $\mu_n \to^w \mu$, which is equivalent with

$\mu_n(f)\to \mu(f)$ for all continuous $f\in \cal C_b(\mathbb{R})$

I've been suggested the following procedure:

  1. Let $\epsilon> 0$, and let $K$ s.t. $F(K)-F(-K)>1-\epsilon$
  2. Approximate a function $f\in \cal C_b(\mathbb{R})$ with piecewise constant function.
  3. Compute integrals of this approximating function and use convergence of the $F_n(x)$ at continuity points of $F$.

    But can't we just say that the set of discontinuities of all $F_n$ and $F$ are at most countable? Then for any interval $I=[x,y]$ where $x,y$ are no discontinuities of any $F_n,F$, conclude that $\mu_n(\textbf{1}_If)\to \mu(\textbf{1}_I f)$

Second, I'm not sure how to approximate this $f$.. thanks in advance for any insight

1 Answers 1

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The idea is the following. Choose $K_1$ and $K_2$ such that $F(K_2)-F(K_1)\geqslant 1-\varepsilon$ and $K_1,K_2$ are not discontinuity points of $F$. For any integer $N$, find an integer $J_N$ and $\{t_N^k\}_{k=1}^{J_N}$ such that $K_1=t_N^1