Average is 2350. Anything above that is technically above average.
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Wait, you forgot to consider split correlation of multi-modal probability distribution functions!
Considering conditional probability of A in respect to B you can obtain a Bayesian estimator for ladder’s intrinsic error, that would allow us to compute the BBATG coefficient for each player and determine if ranks are statistically accurate.
Alternatively we could use the method from Bauszat et al. to construct dense error
prediction from a small set of sparse estimates, that would allow for a better data noise rejection and lead to somewhat more accurate results. It’s much more complicated and computationally intensive tho.
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Rigged is pure comedy gold. For a mad scientist, he has an amazing amount of time to troll the forums.
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Man invented data science and he sits here arguing with rando’s on a video game forum?
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It’s for the greater good. Overwatch has the potential to cure cancer and feed the world.
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I’d almost believe the user if everything they said actually made any sense.
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A serious “mathematician” or computer scientist would at least, out of respect, take the effort to explain complex processes in a generally understandable way. At least that can be attributed to Cuthbert.
Instead, Rigged/Receips/Outside talks completely crazy stuff, because he is seriously delusional or because he wants to distinguish himself as particularly smart.
Since nobody understands his nonsense, of course, one cannot contradict specifically, except that his statements simply do not stand any examination.
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Rigged, I can’t remember if it was you talking about statistics a lot that got me toying with the idea of taking the plunge in that discipline, but if it was, let me offer you a HUGE bit of thanks. I’m only a chapter into Bayesian Statistics and it’s one of the coolest things I’ve ever learned about. The way it’s already changed my thinking about my daily experiences is as quick and profound as it was unexpected.
I see that it could have a lot of applications surrounding the topics of debate on these forums.
Oh but I did! Please don’t jump to conclusions!
Without data we can only assume bounds on the mixture densities.
The only assumption I require is that the lower modalities are of higher variance than the higher modalities. It stands to reason that lower SR gameplay is more volatile and variable whilst higher SR gameplay is more consistent. Is that a fair assumption for the first few moments, and if not, why?
ewww. we’re trying to be param-free dist-free and data-free so that it holds robustly.
and we’re trying to make this computationally efficient.
exactly. we don’t need mcmc denoising lol
No. The reconstruction used by Bauszat et al. (basically a plagiarism from Liu & Zheng) is operationally akin to Sobel filtering and not really applicable here. It requires gradient information and underperforms on fine grained details…like sandbagging your performance during critical moments whilst padding your overall match stats.