Add "method" parameter for yli.regress
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@ -456,7 +456,7 @@ def regress(
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nan_policy='warn',
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nan_policy='warn',
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model_kwargs=None, fit_kwargs=None,
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model_kwargs=None, fit_kwargs=None,
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family=None, # common model_kwargs
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family=None, # common model_kwargs
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cov_type=None, maxiter=None, start_params=None, # common fit_kwargs
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cov_type=None, method=None, maxiter=None, start_params=None, # common fit_kwargs
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bool_baselevels=False, exp=None,
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bool_baselevels=False, exp=None,
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_dmatrices=None,
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_dmatrices=None,
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):
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):
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@ -479,6 +479,7 @@ def regress(
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:type fit_kwargs: dict
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:type fit_kwargs: dict
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:param family: See statsmodels *GLM* constructor
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:param family: See statsmodels *GLM* constructor
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:param cov_type: See statsmodels *model.fit*
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:param cov_type: See statsmodels *model.fit*
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:param method: See statsmodels *model.fit*
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:param maxiter: See statsmodels *model.fit*
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:param maxiter: See statsmodels *model.fit*
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:param start_params: See statsmodels *model.fit*
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:param start_params: See statsmodels *model.fit*
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:param bool_baselevels: Show reference categories for boolean independent variables even if reference category is *False*
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:param bool_baselevels: Show reference categories for boolean independent variables even if reference category is *False*
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@ -534,6 +535,8 @@ def regress(
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fit_kwargs = {}
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fit_kwargs = {}
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if cov_type is not None:
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if cov_type is not None:
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fit_kwargs['cov_type'] = cov_type
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fit_kwargs['cov_type'] = cov_type
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if method is not None:
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fit_kwargs['method'] = method
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if maxiter is not None:
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if maxiter is not None:
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fit_kwargs['maxiter'] = maxiter
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fit_kwargs['maxiter'] = maxiter
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if start_params is not None:
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if start_params is not None:
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