How to use the copulas.univariate.TruncatedGaussian function in copulas
To help you get started, we’ve selected a few copulas examples, based on popular ways it is used in public projects.
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HDI-Project / SDV / sdv / models / copulas.py View on Github 
Copula flatten parameters.
"""
parameters = unflatten_dict(parameters)
parameters.setdefault('fitted', True)
parameters.setdefault('distribution', self.distribution)
parameters = self._unflatten_gaussian_copula(parameters)
for param in parameters['distribs'].values():
param.setdefault('type', self.distribution)
param.setdefault('fitted', True)
self.model = multivariate.GaussianMultivariate.from_dict(parameters)
class GaussianCopulaTruncated(GaussianCopula):
DISTRIBUTION = univariate.TruncatedGaussian
copulas
Create tabular synthetic data using copulas-based modeling.
