Support for fitting parametric margins

[tnagler]

Probably wrapping around https://github.com/JonasMoss/univariateML

But let's keep that for the next release.

[dmi3kno]

Is there a way to relax the requirement that only stats::Distribution can be used in vine_dist() specification of marginals? Would it be possible to look up in the environments and call user supplied function, assuming it is loaded, in the format "mypackage::qdist". Alternatively, if you need both QF and CDF you could either infer the CDF function name from the name of the quantile function or take one more argument.

[tvatter]

Hmmm, that's actually a good idea. @tnagler what do you think?

[ZekeMarshall]

Probably wrapping around https://github.com/JonasMoss/univariateML

But let's keep that for the next release.

Hi all, firstly thank you for creating and maintaining this package - it is fantastic!

It would be great if support for marginal distributions other than those in stats::Distributions could be provided. Specifically, as @tnagler suggests, support for univariateML distributions would be a real help. I use distributions that are found in univariateML but not stats::Distributions extensively, and so it would be really useful to be able to incorporate these marginals into rvinecopulib vine copulae, without needing to defer to marginals present in stats::Distributions with poorer fits.

To get around this, at present I just precompute the marginals using univariateML and feed them to a rvinecopulib::vinecop_dist object, for use by rvinecopulib::pvinecop etc.

Thanks again!

Zeke