I was wondering what the procedure is for deciding if a package should be added to JuliaStats, and, if so, how it is done.
Of the two, DependentBootstrap is probably of greater interest, since bootstrapping time-series is a fairly common operation, and that package is, AFAIK, more complete that just about anything else available in any language (for example, it includes some of the latest techniques in automatic block-length selection, as well as support for multivariate datasets etc). It also is typically faster than any of the comparable R packages (including that one that is implemented in Fortran - the name currently escapes me).
ForecastEval contains code for a Diebold-Mariano test, which is fairly well-known, but the other routines (Reality Check, SPA test, and Model Confidence Set) are a little more niche (although very interesting to someone like me!). EDIT: just noticed the build-status on ForecastEval is failing. I’m not very fluent at Github/Travis, so I’ve obviously stuffed something up there - on the Travis page it looks like the last build passed to me. Weird. The package itself works just fine on v0.6 on my machine with all tests passing.