Sum of two independent random variables converges in distribution [closed]

Solution 1:

I think I got it:

Since $X_n \Rightarrow X_{\infty}$ and $Y_n \Rightarrow Y_{\infty}$, we have $\varphi_{X_n}(t) \to \varphi_{X_\infty}(t)$ for all t, and $\varphi_{Y_n}(t) \to \varphi_{Y_\infty}(t)$ for all $t$ by the continuity theorem. And thus $$ \varphi_{X_n + Y_n} (t) = \varphi_{X_n} (t) \varphi_{Y_n}(t) \to \varphi_{X_\infty}(t)\varphi_{Y_\infty}(t) = \varphi_{X_\infty + Y_\infty}(t)$$ for all $t$. Since both $\varphi_{X_\infty} (t)$ and $\varphi_{Y_\infty}(t)$ are continuous at $0$, $\varphi_{X_\infty + Y_\infty} (t)$ is continuous at $0$. Therefore by continuity theorem we have $X_n + Y_n \Rightarrow X_\infty + Y_\infty$.

Solution 2:

Hint: What happens to the characteristic functions?