 Discrete uniform endpoint posterior

For one uniformly sampled integer $Y\in \{1,\dots ,N\}$, the likelihood function for the unknown endpoint is $N^{-1}{1}_{N\ge y}$. A flat improper prior on positive integers gives an improper posterior distribution, since the harmonic series diverges. A reciprocal prior instead gives a proper posterior proportional to $N^{-2}$ for $N\ge y$, with approximate survival probability $y/n$ and finite quantiles, but infinite posterior mean. A uniform prior cut off at $M$ gives posterior mean $(M-y+1)/(H_M-H_{y-1})\sim M/\log M$, demonstrating sensitivity to that arbitrary cutoff.