> The problem with this is that most programmers don't need statistics on a regular enough basis. That's how things get into standard libraries: people need these things so regularly that there's no point in reimplementing them forever.
True, although I suspect there's probably a certain amount of historical accident to the set of functions included in math.h. There's a strong argument that some of these common 'special' functions are at least as fundamental to a variety of mathematical fields as (say) arc hyperbolic cosine, although admittedly it'd probably be hard to get clear consensus on exact which.
I expect if you asked a variety of stats/ML geeks they might have other priorities to those given here -- e.g. I might request the digamma and trigamma functions (first and second derivatives of log gamma, useful for computing gradients in various Bayesian models) before asking for Bessel functions, say. It might also be sensible to prefer log-domain versions of some of the functions he suggests, since much practical computation with probabilities needs to happen in the log domain.
True, although I suspect there's probably a certain amount of historical accident to the set of functions included in math.h. There's a strong argument that some of these common 'special' functions are at least as fundamental to a variety of mathematical fields as (say) arc hyperbolic cosine, although admittedly it'd probably be hard to get clear consensus on exact which.
I expect if you asked a variety of stats/ML geeks they might have other priorities to those given here -- e.g. I might request the digamma and trigamma functions (first and second derivatives of log gamma, useful for computing gradients in various Bayesian models) before asking for Bessel functions, say. It might also be sensible to prefer log-domain versions of some of the functions he suggests, since much practical computation with probabilities needs to happen in the log domain.