Do Indicator Functions Require Independence of Variables?

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The discussion centers on the mathematical expression involving two random variables, X and Y, and their maximum Z=max{X,Y}. It confirms that the equation E(X-Y)max{X,Y}=E(X-Y)X1{X≥Y}+E(X-Y)Y1{X≤Y} can be written without assuming independence between the variables. A key insight is to modify the inequality from ≤ to < to avoid double-counting the scenario where X equals Y, ensuring the expression holds true for both discrete and continuous variables.

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quema
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Hi,

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



[tex]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\}}[/tex]

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:
[tex]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\}}[/tex]

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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