To be more in line with the rest of the regression families I think it would be a good idea to support loglinear distribution reparameterized with mean and standard deviation on the natural scale.

Here is the reparametrization (from ProbOnto, https://sites.google.com/site/probonto/download):

$P\left(x ; \boldsymbol{\mu}{N}, \boldsymbol{\sigma}{N}\right)=\frac{1}{x \sqrt{2 \pi \log \left

Consider rewriting filter() so that it makes use of two public functions: one to perform mutation and rewrighting, and the other to perform resampling. This added level of control would be useful for latency-sensitive applications that only need to make use of the results from the first stage. After that, resampling could be performed while there is plenty of downtime.

A challenge would be to e