sdv-dev
Bivariate copulas don't scale automatically data for fit
Environment Details
Copulas was installed through mamba in a dedicated environnment, with the conda-forge channel
- Copulas version:0.7.0
- Python version:3.7.12
- Operating System:Windows 10
Error Description
I'm trying to fit a raw 2D set of points with a bivariate copula model, reproducing the behavior of couplas.multivariate.Multivariate (but these classes may actually not be copulas?). It appears that the uniformization of the dataset between 0 and 1 is not handled by fit in the bivariate copulas. For a "user-friendly" experience, it would be great if all steps (distribution fit of X and Y samples, and fit of the copula) were transparent for the user. But maybe the current behavior is wanted?
Steps to reproduce
from copulas.datasets import sample_trivariate_xyz
import copulas.bivariate
data = sample_trivariate_xyz()
data = np.array(data[['x', 'z']])
bi_copula = copulas.bivariate.Gumbel()
bi_copula.fit(data)
ValueError: Marginal value out of bounds.
I have the same issue, it appears that the dataset is expected to be uniformly distributed, which makes no sense mathematically speaking right?
