Hitting a target with a die: finding a better closed form of the recursive formula

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Roll a k-sided die over and over and sum the results. What's the probability that the result will eventually hit exactly n? The recursive formula is:

$$ p_{k,n}= \begin{cases} \begin{array}{cc} 0 & n<0 \\ 1 & n=0 \\ \sum _{x=1}^k \frac{p_{k,n-x}}{k} & n>0 \\ \end{array} \\ \end{cases} $$

Through extremely tedious trial and error, I found the closed form: $$ p_{k,n}= \frac{(k+1)^{n-1}}{k^n}+\sum_{x=1}^{\lfloor{n/(k+1)}\rfloor}(-1)^x\frac{n\cdot (kx+x)^{n-kx-x-1}\cdot x^{kx+x-n}\cdot(n-kx-1)!}{k^{n-kx}\cdot(x-1)!\cdot(n-kx-x)!} $$

Mathematica: closed[k_,n_]:=(k+1)^(n-1)/k^n+Sum[(-1)^y*n*(k*y+y)^(n-k*y-y-1)*y^(k*y+y-n)*(n-k*y-1)!/k^(n-k*y)/(y-1)!/(n-k*y-y)!,{y,1,Floor[n/(k+1)]}]

Does a cleaner closed form exist? Is there a general approach that works well on recursive formulas with multiple base cases?

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Here is a generating function approach. To better see what's going on, we start with a small example.

Example: $k=3, n=2$:

A really small example. We consider a three-sided die and encode the probability to get one, two or three pips as \begin{align*} \frac{z^1+z^2+z^3}{3} \end{align*}

Denoting with $[z^j]$ the coefficient of $z^j$ in a series we obtain \begin{align*} [z^2]&\left(\frac{z+\color{blue}{z^2}+z^3}{3}+\frac{(\color{blue}{z}+z^2+z^3)^2}{9}\right)=\frac{1}{3}+\frac{1}{9}\color{blue}{=\frac{4}{9}} \end{align*} We obtain $n=2$ by either throwing two pips $(2)$ the first time with probability $\frac{1}{3}$ or by throwing one pip twice $(1,1)$ with probability $\frac{1}{9}$ resulting in a total of $\color{blue}{\frac{4}{9}}$. There are no other ways to obtain $n=2$ with a three-sided die.

General case: $k,n$:

We calculate the general case and consider \begin{align*} \color{blue}{[z^n]}&\color{blue}{\sum_{j=1}^\infty\left(\frac{z+z^2+\cdots+z^k}{k}\right)^j}\tag{1}\\ &=[z^n]\sum_{j=1}^\infty\frac{1}{k^j}z^j\left(1+z+\cdots+z^{k-1}\right)^j\tag{2}\\ &=\sum_{j=1}^n\frac{1}{k^j}[z^{n-j}]\left(\frac{1-z^k}{1-z}\right)^j\tag{3}\\ &=\sum_{j=1}^n\frac{1}{k^j}[z^{n-j}]\sum_{r=0}^\infty\binom{-j}{r}(-z)^r\sum_{s=0}^j\binom{j}{s}\left(-z^k\right)^s\tag{4}\\ &=\sum_{j=1}^n\frac{1}{k^j}[z^{n-j}]\sum_{t=0}^\infty \sum_{{{r+ks=t}\atop{r\geq 0}}\atop{0\leq s\leq j}}\binom{j+r-1}{j-1}\binom{j}{s}(-1)^sz^t\tag{5}\\ &=\sum_{j=1}^n\frac{1}{k^j}[z^{n-j}]\sum_{t=0}^\infty \sum_{s=0}^{\min\left\{j,\left\lfloor\frac{t}{k}\right\rfloor\right\}}\binom{j+t-ks-1}{j-1}\binom{j}{s}(-1)^sz^t\tag{6}\\ &\,\,\color{blue}{=\sum_{j=1}^n\frac{1}{k^j} \sum_{s=0}^{\min\left\{j,\left\lfloor\frac{t}{k}\right\rfloor\right\}}\binom{n-ks-1}{j-1}\binom{j}{s}(-1)^s}\tag{7} \end{align*} which is similar to OPs formula, admittedly slightly more complex due to the double sum (see below).

Comment:

  • In (1) we use the Ansatz from the small example. Here we allow $j\geq 1$ throws without any harm, since the coefficient of operator $[z^n]$ guarantees, that terms with powers of $z$ greater than $n$ will be skipped.

  • In (2) we factor out $z^j$.

  • In (3) we apply the rule $[z^{p-q}]A(z)=[z^p]z^qA(z)$ and use the finite geometric sum formula. We also set the upper limit $n$ since other indices do not contribute.

  • In (4) we use the binomial series expansion and apply the binomial theorem.

  • In (5) we use the Cauchy product of two pwer series. We also use the binomial identity $\binom{-p}{q}=\binom{p+q-1}{p-1}(-1)^q$.

  • In (6) we eliminate $r$ by substituting $r=t-ks$.

  • In (7) we select the coefficient of $z^{n-j}$.

OPs formula:

We can transform OPs formula writing $j$ instead of $x$ for convenience only and obtain \begin{align*} p_{k,n}&= \frac{(k+1)^{n-1}}{k^n}\\ &\ +\sum_{j=1}^{\lfloor{n/(k+1)}\rfloor}(-1)^j\frac{n\cdot (kj+j)^{n-kj-j-1}\cdot j^{kj+j-n}\cdot(n-kj-1)!}{k^{n-kj}\cdot(j-1)!\cdot(n-kj-j)!}\\ &=\frac{(k+1)^{n-1}}{k^n}\\ &\ +\sum_{j=1}^{\lfloor{n/(k+1)}\rfloor}(-1)^j\frac{n(k+1)^{n-kj-j-1}j^{-1}}{k^{n-kj}}\binom{n-kj-1}{j-1}\tag{8}\\ \end{align*} In the last line we factored out $j$ and cancelled powers of $j$. We also use $\binom{p}{q}=\frac{p!}{q!(p-q)!}$.

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Here's one option: represent the recursive formula as a $k\times k$ matrix:

$$ M_{k,n}= \begin{bmatrix} \frac{1}{k} & \frac{1}{k} & \cdots & \frac{1}{k} & \frac{1}{k} \\ 1 & 0 & \cdots & 0 & 0 \\ 0 & 1 & \cdots & 0 & 0 \\ \vdots & \vdots & \ddots & \vdots & \vdots \\ 0 & 0 & \cdots & 1 & 0 \end{bmatrix}^n $$ The probability is the first element of the matrix. $$ p_{k,n}=(M_{k,n})_{0,0} $$

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(WARNING : not an answer to the question, but too long for a comment):

Fixed $n$ formula are tough, but their asymptotic in this case remains simple:

As $n$ gets large, for $k$ fixed, $p_{k,n}$ converges toward the inverse of the expected value of the dice, so $2/(k+1)$ for a $k$-dice.

Check Blackwell renewal theorem, arithmetic case for this kind of limit statement : https://encyclopediaofmath.org/wiki/Blackwell_renewal_theorem