Bigsimr.jl VS OffsetArrays.jl

One more example for you. Our group wrote our core package in Julia called Bigsimr.jl (here) and then wrote interfaces to it for R (here and on cran) and Python (here and on PyPi)

Mostly, but I used it to write a package that does multivariate simulation via gaussian copulas with correlation matching. You can find it here.

We wrote a Julia package that can do this called Bigsimr which also has an R interface. Message me if you have more questions.

I wrote a Julia library that basically applies this idea, but extends it to multivariate distributions. We sample from a multivariate normal, transform the margins to uniform (via the normal cdf), and then transform to the desired distribution using the margins inverse cdf's (called the NORTA algorithm). The caveat is that this transformation is non-linear, so the correlation matrix used to generate the multivariate normal samples is generally not the same as the correlation after transformation. We account for this by numerically solving for the n*(n-1)/2 double integrals to determine what input correlation is necessary to get the desired output correlation. This paper describes the full problem and method for solving.

Well, there is OffsetArrays in Julia, but it has acquired a reputation as a poison pill because most code assumes the 1-based indexing and it's easy to forget to convert the indexing and screw up the code.

Similar correctness issues are a big part of the reason that, several years ago, I submitted a series of pull requests to Julia so that its entire test suite would run without memory errors under Valgrind, save for a few that either (i) we understood and wrote suppressions for, or (ii) we did not understand and had open issues for. Unfortunately, no one ever integrated Valgrind into the CI system, so the test suite no longer fully runs under it, last time I checked. (The test suite took nearly a day to run under Valgrind on a fast desktop machine when it worked, so is infeasible for every pull request, but could be done periodically, e.g. once every few days.)

Even a revived effort on getting core Julia tests to pass under Valgrind would not do much to help catch correctness bugs due to composing different packages in the ecosystem. For that, running in testing with `--check-bounds=yes` is probably a better solution, and much quicker to execute as well. (see e.g. https://github.com/JuliaArrays/OffsetArrays.jl/issues/282)

You might be interested in OffsetArrays.jl.

Counting starts at one, as do most vector/matrix/tensor indices. If it bothers you too much, see OffsetArrays.jl and Arrays with custom indices.

No need for another version, Julia supports custom indices by default. Check out https://docs.julialang.org/en/v1/devdocs/offset-arrays/ and https://github.com/JuliaArrays/OffsetArrays.jl