GaussianCopula.fit
Fit the data with a Gaussian copula, i.e.: compute the univariate distribution for each variable and then its covariance matrix.
GaussianCopula.fit(data, [marginal_dist_dict, ])
Parameters
- data: (dataframe)
- dataframe that contains the two columns
- marginal_dist_dict: (dict)
- A dictionary where keys are variable names and values are lists of candidate marginal distributions. Defaults to
None.
- A dictionary where keys are variable names and values are lists of candidate marginal distributions. Defaults to
Returns
None. Updates attributes GaussianCopula.correlation, GaussianCopula.univariates.
Notes
Examples
Please refer to the below pages for detailed examples:
| Example | Description |
|---|---|
| GaussianCopula | Demonstrates use of GaussianCopula to create multivariate synthetic data. |