For many of the numerical methods in that package, people weren't sure if the code in question would generate reasonable results for other types. Some of it probably does, but it's not trivially true that evaluating those distribution on high-precision floats would produce correct results.
On Friday, June 19, 2015 at 8:59:41 AM UTC-7, Xiubo Zhang wrote: > > I have been reading the source code for Distributions.jl, and had noted > that functions such as "pdf" are defined over (d::Normal, x::Float64) (for > Normal distribution, for example) rather than (d::Normal, x::Real). The > manual of Julia recommended that more general types be used over specific > types when possible; also it seems one of the major features of the > language is the smart type inferencing which eliminates the needs to use > very specific types. > > So my question really is, what is the rationale behind the decision of > using specific types over abstract types? What are the advantages and > disadvantages? >
