Convergence in probability of the sum of two random variables

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SUMMARY

The discussion focuses on proving the convergence in probability of the sum of two random variables, specifically that if \(X_n \xrightarrow{\text{P}} X\) and \(Y_n \xrightarrow{\text{P}} Y\), then \(X_n + Y_n \xrightarrow{\text{P}} X + Y\). The proof utilizes the triangle inequality and the properties of probability measures, demonstrating that the probability of the event \(D_n(\epsilon) = \{|X_n - X + Y_n - Y| < 2\epsilon\}\) approaches 1 as \(n\) approaches infinity. The argument is structured around the sets \(A_n(\epsilon)\) and \(B_n(\epsilon)\), leading to the conclusion that the sum of the two sequences converges in probability.

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Gregg
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Homework Statement



X, Y, (X_n)_{n&gt;0} \text{ and } (Y_n)_{n&gt;0} are random variables.

Show that if

X_n \xrightarrow{\text{P}} X and Y_n \xrightarrow{\text{P}} Y then X_n + Y_n \xrightarrow{\text{P}} X + Y

Homework Equations



If X_n \xrightarrow{\text{P}} X then \text{Pr}(|X_n-X|&gt;\epsilon)=0 \text{ } \forall \epsilon &gt; 0 \text{ as } n \to \infty

The Attempt at a Solution



First, let the sets A_n(\epsilon) = \{|X_n - X|&lt;\epsilon\} and B_n(\epsilon) = \{|Y_n - Y|&lt;\epsilon\}

The sum of the two moduli will always be less than 2\epsilon if both of the moduli are less than \epsilon but the converse is not generally true.

C_n(\epsilon)=\{|X_n-X|+|Y_n-Y|&lt;2\epsilon\}\supset{A_n(\epsilon)\cap B_n(\epsilon)}


Using the triangle inequality:
|X_n + Y_n - X - Y | \le |X_n-X|+|Y_n-Y|


D_n(\epsilon) =\{|X_n-X+Y_n-Y|&lt;2\epsilon\} \supset C_n(\epsilon)


I think this has gone wrong in several places but from here I hope to say that

\text{Pr}(D_n) \ge \text{Pr}(C_n) \ge \text{Pr}(A_n\cap B_n ) \ge \text{Pr}(A_n) \to 1 \text{ as } n\to\infty

\text{Pr}(D_n^c) \to 0 \text{ as } n\to \infty
 
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You can always consider n' so that both
## |X_n -X| < \epsilon/2 ,|Y_n -Y| < \epsilon/2 ##, so that

For## Z_n := X_n + Y_n ; Z=X+Y ##

## |Z_n -Z| =| X_n -X + Y_n -Y| \leq |X_n -X|+|Y_n -Y| < \epsilon/2 + \epsilon/2 =\epsilon##

So that ##X_n + Y_n ## converges to ## X+Y ##
 

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