What is the expected value of the absolute standardized t-distribution - i.e.,: $E(|X|)$, where $X$ has the standardized t-distribution?
-
1There are two close votes now, "needs details or clarity". I don't quite see what is unclear about this question. Could close-voters please comment on what clarification they would like to see? – Stephan Kolassa May 14 '20 at 19:27
1 Answers
Per whuber's answer to Standardized Student's-t distribution, the density of the standardized $t$ distribution on $\nu$ degrees of freedom is
$$f(x) = \frac{\Gamma(\frac{\nu + 1}{2})}{\Gamma(\frac{\nu}{2})} \frac{1}{\sqrt{\pi(\nu-2)}} \left[1+\frac{x^2}{\nu-2}\right]^{-\frac{\nu+1}{2}}.$$
(Note that we need $\nu>2$ so we have two moments to standardize.)
Thus, your expectation is
$$ \begin{align*} E(|X|) & = 2\int_0^\infty xf(x)\,dx \\ & = \frac{\Gamma(\frac{\nu + 1}{2})}{\Gamma(\frac{\nu}{2})} \frac{2}{\sqrt{\pi(\nu-2)}} \int_0^\infty x\left[1+\frac{x^2}{\nu-2}\right]^{-\frac{\nu+1}{2}}\,dx \\ &= \frac{\Gamma(\frac{\nu + 1}{2})}{\Gamma(\frac{\nu}{2})} \frac{2}{\sqrt{\pi(\nu-2)}} \left(-\frac{\nu-2}{\nu-1}\right)\left(1+\frac{x^2}{\nu-2}\right)^{\frac{1-\nu}{2}}\bigg|_0^\infty \\ & = \frac{2}{\sqrt{\pi}}\frac{\Gamma(\frac{\nu + 1}{2})}{\Gamma(\frac{\nu}{2})} \frac{\sqrt{\nu-2}}{\nu-1} \end{align*} $$ by a rather simple integral evaluation.
I like sanity checking calculations like these using simulation, and it seems to check out:
> df <- 10
> nn <- 1e6
>
> sims <- rt(nn,df)/(sqrt(df/(df-2)))# standardize by the variance
> mean(sims)
[1] -0.0006262779
> var(sims)
[1] 0.9995302
>
> mean(abs(sims))
[1] 0.7732408
> 2/sqrt(pi)*gamma((df+1)/2)/gamma(df/2)*sqrt(df-2)/(df-1)
[1] 0.773398

- 95,027
- 13
- 197
- 357
-
-
1+1. This works for any $\nu \gt 2;$ it is not necessary that $\nu \ge 3.$ – whuber May 14 '20 at 20:35
-