Let:
$$f(y) = \sum_{x=y}^{\infty} {x \choose y} \left(\frac{1}{3}\right)^{x+1}$$
Can this be simplified somehow? Is it a standard probability distribution?
I can only get as far as:
$$f(y) = \frac{1}{3} \sum_{x=y}^{\infty} \frac{x!}{y!(x-y)!} \left(\frac{1}{3}\right)^{x}$$
This arose in the context of a probability problem in which X is a geometrically distributed random variable ($p=1/2$) and $Y$ is a binomially distributed random variable ($p=1/2$, $n=x$)
Use the generalized binomial theorem $(1-z)^{-s} =\sum_{k=0}^{\infty} \binom{k+s-1}{s-1}z^k =\sum_{k=s-1}^{\infty} \binom{k}{s-1}z^{k-s+1} =z^{-s+1}\sum_{k=s-1}^{\infty} \binom{k}{s-1}z^{k} $ so that $\sum_{k=s-1}^{\infty} \binom{k}{s-1}z^{k} =z^{s-1}(1-z)^{-s} $ or $\sum_{k=u}^{\infty} \binom{k}{u}z^{k} =z^{u}(1-z)^{-u-1} $.
See, for example, here: https://en.wikipedia.org/wiki/Binomial_theorem
Then
$\begin{array}\\ f(y) &= \sum_{x=y}^{\infty} {x \choose y} \left(\frac{1}{3}\right)^{x+1}\\ &= \frac13\sum_{x=y}^{\infty} {x \choose y} \left(\frac{1}{3}\right)^{x}\\ &=\frac13(\frac13)^{y}(1-\frac13)^{-y-1}\\ &=(\frac13)^{y+1}(\frac23)^{-y-1}\\ &=(\frac12)^{y+1}\\ \end{array} $