With partial integration I wanted to prove that for non-negative random variable with CDF F(x) holds
∫∞0¯F(x)dx=E[X].
Here is ¯F(x)=1−F(x). I got this far
∫∞0¯F(x)dx=lim
But now I don't know hot to calcute the upper limit.
Does anyone have a clue how to prove this?
Have a nice day!
Answer
Since \bar{F}(x) = 1- \mathbb{P}(X \leq x) = \mathbb{P}(X>x), we have
x \bar{F}(x) = \int_{\{X>x\}} x \, d\mathbb{P} \leq \int_{\{X>x\}} X \, d\mathbb{P}
for any x>0. If \mathbb{E}(X)<\infty, then we can let x \to \infty using the dominated convergence theorem to conclude
\lim_{x \to \infty} x \bar{F}(x)=0.
If \mathbb{E}(X)=\infty then x \bar{F}(x) does not necessarily converge to 0 as x \to \infty (consider for example a random variable with Cauchy distribution).
A remark concerning your proof: Mind that you have to assume the existence of a density, i.e. your proof works only for random variables which have a density with respect to Lebesgue measure.
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