Hi everyone,
I’ve just released ScientificFitting.jl v0.1, my first public Julia package. It aims to make statistically careful scientific fitting fast to write and enjoyable to use, without hiding uncertainty models or diagnostic evidence when fits become difficult.
pkg> add ScientificFitting
It currently provides weighted nonlinear least squares and likelihood fits, explicit x/y and correlated uncertainties, parameter constraints, multi-dataset fits, actionable diagnostics, profile likelihoods, confidence regions, and optional editable Makie figures. The numerical core works without Makie.
This is intentionally an early work-in-progress release. I would be very happy to hear your thoughts and wishes for future versions, especially from people trying it on real analyses. If you encounter numerical edge cases, unclear diagnostics, awkward API choices, documentation or plotting problems, or a missing scientific workflow, please reply here or open an issue. Contributions and example datasets are very welcome as well.
Two little examples from the docs:
