It took a while, but it's here.
What is SPRITE? It's a tool for turning descriptive statistics in a scientific paper into plausible distributions.
The preprint is attached.
But mainly: we can investigate published papers with no raw data for plausibility. Basically, SPRITE lets you see what lies beneath the surface-level descriptions of a scientific result. (Sometimes, of course. Not all the time.)
If you make up an impossible mean/SD, SPRITE will flag it. If you make up implausible data, SPRITE can find it. Again, not all the time. But enough.
Q: "Is it like GRIM?"
A: It's related, yes. GRIM tells you if a mean can exist (GRIMMER tells you if an SD can exist or not). SPRITE tells you *if the mean/SD can exist, what does it look like?*
It means you can SEE the data, not just consistency-check it.
And I honestly don't think it's fully optimized, even in its present state.
A: not *really*. It's more complicated than when I first wrote about it (attached). But it's still conceptually similar: (a) we make a fake sample with the right mean (b) we shuffle values between bins until we have the right SD.
A: Not the soft drink. A 'sprite' is an elf or a pixie, & how I imagined the code originally - jumping around, fast and weightless, until it solved. It's small, quick, flexible, and multi-talented.
And I couldn't make 'Tinkerbell' into an acronym.
A: Well, I hope people use it. Find that paper you don't understand, or don't trust. Try to reproduce its distributions. Look *inside* the numbers.
I'd like to think this *isn't* because researchers don't care. Bad research obviously bothers most researchers.