5 ms·

If the user doesn't know how many unique items there are, they would need to keep refreshing even longer to gauge whether the N they've seen is the full set.

• gregdaniels421 2mo ago
  Is there a good way to determine after seeing N unique items in M trials how many items there potentially are? Would tracking the time between seeing new unique items help? Is this an already solved problem?
  • clickety_clack 2mo ago
    This is the “German tank problem”: https://en.wikipedia.org/wiki/German_tank_problem?wprov=sfti1 https://en.wikipedia.org/wiki/German_tank_problem?wprov=sfti...
    • senderista 2mo ago
      No, it's not the same as the German tank problem, because that assumes all sampled values are unique (and totally ordered). It's closer to the "species richness" estimation problem, where you estimate the total number of species from a sample (specimens) with many repeated values (species).
      • clickety_clack 2mo ago
        Ah, you’re right! The German tank problem was based on reading the serial numbers I think.
  • senderista 2mo ago
    There are many different statistical estimators for this problem, many from the ecology literature (e.g. Chao1). This paper and a Python library based on it covers many of them: https://www.vldb.org/conf/1995/P311.PDF https://www.vldb.org/conf/1995/P311.PDF https://pydistinct.readthedocs.io/en/latest/docs/readme_link.html https://pydistinct.readthedocs.io/en/latest/docs/readme_link...