logstatsexp

[cossio]

Adds the functions logmeanexp, logvarexp, logstdexp

[cossio]

These functions are usually useful for me, thought it'd be nice to have them here.

Not sure why CI is failing on Julia 1.0 ?

[longemen3000]

I don't have an strong opinion on this, but Is it possible to implement this as an extension? This package is a really low level one, and adding a new dependency could have effects on downstream packages? The same thing applies to LinearAlgebra, (but they should be it's own issue)

[cossio]

@longemen3000 The PR is not introducing any dependencies.

[longemen3000]

Statistics, while a Stdlib, it is a new dependency

[longemen3000]

Ohhh, nvm, my error, in that case, no comment at all

[cossio]

@longemen3000 Yes but Statistics is only used in tests

[cossio]

CI passing now.

@devmotion I agree the implementation is not optimal but I don't have time to tune it now. Could we merge as it is now?

[ParadaCarleton]

I think we can merge now and work on optimization later.

Honestly, it's just a huge pain trying to optimize for allocations without having Transducers.jl, laziness, or good functional primitives in Julia.

[devmotion]

@ParadaCarleton as far as I know you've never contributed to this package, so I really think that you should let the maintainers of this package decide when a PR is ready and can be merged. In my opinion, being a member of JuliaStats doesn't mean that you are able and should merge PRs in repos that you haven't contributed to and/or are not familiar with. For instance, there are many JuliaStats packages where I don't think it's appropriate for me to merge PRs.

[devmotion]

Clearly, we should not over-optimize this PR. But at the same time we should hold off merging PRs if reviewer comments that can be addressed without too much effort are not resolved. For instance, I think currently the following things are missing in this PR:

• Definitions for non-AbstractArray inputs (it seems the same algorithm could be applied?)
• Avoiding allocating R .- log(N) etc. when R is an Array and broadcasting when R is a scalar
• Tests with non-Float64 inputs (these would have uncovered the promotion issues)