Do Indicator Functions Require Independence of Variables?

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The discussion revolves around the relationship between two random variables, X and Y, and the expression involving their maximum, Z. It is clarified that the equation E(X-Y)max{X,Y} can be rewritten without assuming independence of the variables. A suggestion is made to adjust the inequality from <= to < to avoid double-counting when X equals Y. The conclusion emphasizes that the expression holds true for both dependent and independent variables, applicable to various types of distributions. The focus remains on the mathematical validity of the expression rather than the independence of X and Y.
quema
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Hi,

If X and Y are two random variables. Let Z=max\left\{{X,Y}\right\}. Can I write:



E(X-Y)max\left\{{X,Y}\right\}=E(X-Y)X1_{\left\{{X\geq{}Y}\right\}}+E(X-Y)Y1_{\left\{{X\leq{}Y}\right\}}

Do I need to assume that both random variables are independent?

Thanks.
 
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Hi quema! :smile:

I think you can always write that! I'm not sure what you're trying to do, though...
 
quema said:
Can I write:
E(X-Y)max\left\{{X,Y}\right\}=E(X-Y)X1_{\left\{{X\geq{}Y}\right\}}+E(X-Y)Y1_{\left\{{X\leq{}Y}\right\}}

Change the <= to < so you're not double-counting the case where X=Y, and it'll hold true regardless of dependence or whether they are discrete or continuous.
 
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