statsmodels.regression.linear_model.GLS.from_formula
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classmethod GLS.from_formula(formula, data, subset=None, *args, **kwargs)
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Create a Model from a formula and dataframe.
Parameters: formula : str or generic Formula object
The formula specifying the model
data : array-like
The data for the model. See Notes.
subset : array-like
An array-like object of booleans, integers, or index values that indicate the subset of df to use in the model. Assumes df is a
pandas.DataFrame
args : extra arguments
These are passed to the model
kwargs : extra keyword arguments
These are passed to the model with one exception. The
eval_env
keyword is passed to patsy. It can be either apatsy.EvalEnvironment
object or an integer indicating the depth of the namespace to use. For example, the defaulteval_env=0
uses the calling namespace. If you wish to use a ?clean? environment seteval_env=-1
.Returns: model : Model instance
Notes
data must define __getitem__ with the keys in the formula terms args and kwargs are passed on to the model instantiation. E.g., a numpy structured or rec array, a dictionary, or a pandas DataFrame.
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