Comments (4)
Ah @kaleb-keny! Sorry I missed your post! (It's a busy time at work before we wind down for Christmas)
Let me take a look at it over the weekend and get back to you on this
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Hey, I just want to thank you as well for making this package... I am really impressed by the high quality of of coding that went into it... Also the use of numpy helps speed up the calculation by a large extent compared to other copula packages on python....
So in the end, I just want to put an update on this, I did end up using a GumbelCopula which worked pretty well on the data...
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I think the issue should be fixed with version 0.7.1
from copulae.
Yeah I it ran without issue.. Although 😅 I will need to do some experimentation, as I just can't seem to get the same level of linearity as the one obtained empirically...
thank you though, appreciate that you build this package and maintained it for us python users...
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Related Issues (20)
- Question about BaseCopula.random() Method HOT 1
- EmpiricalCopula does not work HOT 2
- Copula Fit Replication with SAS using Uniform Marginals HOT 2
- Error after update HOT 2
- Designation of p_obs does not affect the fit HOT 2
- the summary( ) got converging error HOT 2
- ModuleNotFoundError: No module named 'copulae.special._specfunc' HOT 2
- Python 3.6 not supported? HOT 4
- How to Inverse Normalisation?[Quantile Function] HOT 2
- Fixing Correlation Matrix if copulae.fit() HOT 2
- test_gmc failures HOT 1
- Feature Request - Plot a copula
- Gaussian Mixture Copula Model gives wrong sampling
- Frank and Gaussian Copula give Error
- PEP 517 builds HOT 1
- Ver 0.7.7 - Kendall Tau not supported for Student Copula HOT 1
- Fit Summary HOT 1
- Support for discrete marginals
- Thank you! HOT 2
- An error occurred while importing copulae HOT 2
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