Thursday, 22 October 2015

Proof verification : XntoX in distribution, Ynto0 in probability implies XnYnto0 in probability



I have to show : XnX in distribution, Yn0 in probability XnYn0 in probability.




Let α>0,ϵ>0. Then δ>0 such that ϵ/δ, ϵ/δ are continuity points of distribution of X and P(|X|>ϵ/δ)α



Since XnX in distribution, P(Xnx)P(Xx) for all continuity points (and in particular ϵ/δ and ϵ/δ). There exists N1,N2N such that
nN1|P(Xnϵ/δ)P(Xϵ/δ)|<α
nN2|P(Xnϵ/δ)P(Xϵ/δ)|<α
Let N=max. Then for n \geq N,




P(|X_n|>\epsilon/\delta)=1-P(|X_n| \leq \epsilon/\delta)=1-P(-\epsilon/\delta \leq X_n \leq \epsilon/\delta) = 1-P(X_n \leq \epsilon/\delta)+P(X_n < -\epsilon/\delta) = 1-P(X_n \leq \epsilon/\delta)+P(X_n \leq -\epsilon/\delta \,\,[\text{by continuity}] \leq 1-P(X \leq \epsilon/\delta)+P(X \leq -\epsilon/\delta)+2\alpha = P(|X|>\epsilon/\delta)+2\alpha \leq 3\alpha



Since Y_n \to 0 in probability, \exists N_3 \in \mathbb{N} such that
n \geq N_3 \implies P(|Y_n|>\delta) \leq \alpha



Choose N^{*}=\max\{N,N_3\}. Note that
|X_nY_n|>\epsilon \implies |X_n|>\epsilon/\delta \,\,\text{or}\,\, |Y_n|>\delta
Hence,
P(|X_nY_n|>\epsilon) \leq P(|X_n|>\epsilon/\delta \,\,\text{or}\,\, |Y_n|>\delta) \leq P(|X_n|>\epsilon/\delta)+P(|Y_n|>\delta)

Thus,
n \geq N^{*} \implies P(|X_nY_n|>\epsilon) \leq 4\alpha
Since, \alpha>0 is arbitrary, X_nY_n \to 0 in probability.




Is the proof okay? I have a feeling that I have sort of over-killed it. Is it possible to write a shorter proof of the result? Thank you.


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