kernel density is important

Until a couple versions ago, in my main gun, I was using Gaussian until a certain number of data points, then switching to if (abs(ux) < 1) { density += square(1 - square(ux)) }. After some testing with WaveSim, I'm now using (1 - cube(abs(ux))) and never using Gaussian. YMMV, but I think with the amount of data you have in a gun, you don't really need the heavy smoothing offered by formulas that cover the whole range.

One less intensive approach that covers the whole range would be something like: density += 1.0 / (1 + square(ux)), which is akin to what a lot of VCS guns do for Bin Smoothing.