Hi Guile Users! I recently wrote a little program involving lots of uniformly distributed random integers. For that I used SRFI-27 and it works fine.
Then I thought: How would I get normal distributed random numbers? I don't have a project or program in mind for this, but it struck me, that I do not know, how to get a normal distribution from a uniform distribution. So I dug into the matter … Turns out the math is not really my friend: * https://stackoverflow.com/a/3265174 – OK, if that's true, then don't use Box-Muller-Transform * https://stackoverflow.com/a/86885 – The what? I need to somehow inverse the Gaussian distribution to get a function to calculate normal distributed values from uniformly distributed values? Something like that. Safe to say it is above my current math skills. * The wiki page also does not help me much: https://en.wikipedia.org/wiki/Inverse_transform_sampling Seems too complicated. So I thought: "OK, maybe I can simply copy, how other languages implement it!" The wiki page mentions, that R actually makes use of the inverse thingy. So I set out to look at R source code: * https://github.com/wch/r-source/blob/master/src/nmath/rnorm.c – OK, looks simple enough … Lets see what `norm_rand` is … * https://github.com/wch/r-source/blob/master/src/nmath/snorm.c#L62 – yeah … well … I'm not gonna implement _that_ pile of … Just look at the lines https://github.com/wch/r-source/blob/master/src/nmath/snorm.c#L135-L196 what a mess! Not a single comment to help understanding in it. Such a disappointment. * Python also seems to only use an approximation with magic constants: https://github.com/python/cpython/blob/3.8/Lib/random.py#L443 So it seems, that there is no easy way to implement it properly with correct tails to the left and right side of the distribution, something clean and not made with mathematical traps built-in. Or is there? I found a post about using 2 normal distributions to do Box-Muller-transform: https://www.alanzucconi.com/2015/09/16/how-to-sample-from-a-gaussian-distribution/ However, it seems to require a uniform float not integer and it is the Box-Muller-transform, which is said to clamp between -6 and 6 according to the people writing the answers on stackoverflow. So my question is: Is there a good implementation in the Guile universe already? (Or a simple way to implement it?) I don't really need it right now, but I think this thing could be an obstacle for many people without serious math knowledge and it would be good to know, where to find it, should one have need for normal distributed random numbers. Regards, Zelphir
