Is the Finite Expectation of Powers Satisfied by Nonnegative Random Variables?

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The discussion centers on the condition for the finite expectation of powers of nonnegative random variables, specifically stating that for a nonnegative random variable X and p in the range (0, ∞), the expectation E[X^p] is finite if and only if the series ∑(n=1 to ∞) n^(p-1) P(X ≥ n) converges. Participants clarify that X is not required to have a density function, which is crucial for understanding the relationship between the expectation and the series. The conversation highlights the equivalence of the integral and the series when X is a positive integer.

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Euge
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Suppose ##X## is a nonnegative random variable and ##p\in (0,\infty)##. Show that ##\mathbb{E}[X^p] < \infty## if and only if ##\sum_{n = 1}^\infty n^{p-1}P(X \ge n) < \infty##.
 
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\mathbb{E}[X^p] =\int_0^\infty x^p p(x) dx = [ x^p \sigma(x)]_0^\infty - p \int_0^{\infty} x^{p-1}\sigma(x) dx
= p \int_0^{\infty} x^{p-1}(1-\sigma(x) )dx
where
\sigma(x)=\int_0^x p(t) dt,\ \ \sigma(\infty)=1
The integral differs from the given series by finite quantity. They both are finite or infinite.
 
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anuttarasammyak said:
\mathbb{E}[X^p] =\int_0^\infty x^p p(x) dx = [ x^p \sigma(x)]_0^\infty - p \int_0^{\infty} x^{p-1}\sigma(x) dx
= p \int_0^{\infty} x^{p-1}(1-\sigma(x) )dx
where
\sigma(x)=\int_0^x p(t) dt,\ \ \sigma(\infty)=1
The integral differs from the given series by finite quantity. They both are finite or infinite.
I think the tricky part of this problem is showing your second to last sentence. A non-answer spoiler:
Euler-Maclaurin with one of the limits going to infinity has to be treated carefully
 
Hi @anuttarasammyak, in this problem ##X## is not assumed to have a density.
 
Euge said:
Hi @anuttarasammyak, in this problem ##X## is not assumed to have a density.
I see. If X is a positive integer I hope the replacement
p(x)=\sum_{n=1}^{\infty}\ P_n\ \delta(x-n)
where n is positive integer and
\sum_{n=1}^{\infty}P_n=1,0 \leq P_n
would work in my previous post. The integral and the series coincide.
 
Last edited:

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