Let $X\sim NB(r,p)$ and $Y\sim NB(s,p)$ be negativ binomials (I use the variant where we count all trials until we reach r successes). Further, they are independent and I am interested in the distribution of $X+Y$. Surely enough, the result is a Negative Binomial again with parameter r+s.
The task however was to prove that using only the convolution formula. Doing that I derived the following
$$P(X+Y=n)=p^{r+s}(1-p)^{n-r-s}\sum_{j=0}^{n-r-s}\binom{n-j-s-1}{r-1}\binom{j+s-1}{s-1}$$
Since I know the result, I know that this holds:
$$\sum_{j=0}^{n-r-s}\binom{n-j-s-1}{r-1}\binom{j+s-1}{s-1}=\binom{n-1}{r+s-1}$$
Does anyone recognize this identity? I would love it if there was a combinatorial proof for it.
EDIT: Thanks to a comment I adapted the combinatorial argument as follows:
We use m objects and choose one object out of m that splits the list of all objects in two halfs. Then we choose x from the left half and y from the right half.
Another way of counting is to choose element j in the list, choosing x from j-1 elements on the left and y from m-j-1 objects from the right half. Obviously j can run only from x+1 to m-y-1. Therefore $$\binom{m}{x+y+1}=\sum_{j=x+1}^{m-y-1}\binom{j-1}{x}\binom{m-j+1}{y} =\sum_{k=0}^{m-x-y}\binom{k+x}{x}\binom{m-k-x}{y}$$ Choosing m=n-2, x=s-1, y=r-1 gives the desired result.