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Merge pull request statsmodels#727 from jseabold/fix-709
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DOC: Fix indent and add missing params to linear models. Closes statsmodels#709.
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jseabold committed Mar 26, 2013
2 parents 203ab96 + 345d7fa commit f6df25d
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Showing 3 changed files with 7 additions and 7 deletions.
6 changes: 3 additions & 3 deletions statsmodels/base/model.py
Expand Up @@ -23,9 +23,9 @@
_missing_param_doc = """missing : str
Available options are 'none', 'drop', and 'raise'. If 'none', no nan
checking is done. If 'drop', any observations with nans are dropped.
If 'raise', an error is raised. Default is 'none.'"""
_extra_param_doc = """
hasconst : None or bool
If 'raise', an error is raised. Default is 'none.'
"""
_extra_param_doc = """hasconst : None or bool
Indicates whether the RHS includes a user-supplied constant. If True,
a constant is not checked for and k_constant is set to 1 and all
result statistics are calculated as if a constant is present. If
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6 changes: 3 additions & 3 deletions statsmodels/regression/linear_model.py
Expand Up @@ -249,7 +249,7 @@ class GLS(RegressionModel):
>>> print gls_results.summary()
""" % {'params' : base._model_params_doc,
'extra_params' : base._extra_param_doc}
'extra_params' : base._missing_param_doc + base._extra_param_doc}

def __init__(self, endog, exog, sigma=None, missing='none', hasconst=None):
#TODO: add options igls, for iterative fgls if sigma is None
Expand Down Expand Up @@ -370,7 +370,7 @@ class WLS(RegressionModel):
statistics such as fvalue and mse_model might not be correct, as the
package does not yet support no-constant regression.
""" % {'params' : base._model_params_doc,
'extra_params' : base._extra_param_doc}
'extra_params' : base._missing_param_doc + base._extra_param_doc}

def __init__(self, endog, exog, weights=1., missing='none', hasconst=None):
weights = np.array(weights)
Expand Down Expand Up @@ -472,7 +472,7 @@ class OLS(WLS):
-----
No constant is added by the model unless you are using formulas.
""" % {'params' : base._model_params_doc,
'extra_params' : base._extra_param_doc}
'extra_params' : base._missing_param_doc + base._extra_param_doc}
#TODO: change example to use datasets. This was the point of datasets!
def __init__(self, endog, exog=None, missing='none', hasconst=None):
super(OLS, self).__init__(endog, exog, missing=missing,
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2 changes: 1 addition & 1 deletion statsmodels/tsa/base/tsa_model.py
Expand Up @@ -32,7 +32,7 @@
class TimeSeriesModel(base.LikelihoodModel):

__doc__ = _tsa_doc % {"model" : _model_doc, "params" : _generic_params,
"extra_params" : base._missing_param_doc}
"extra_params" : _missing_param_doc}

def __init__(self, endog, exog=None, dates=None, freq=None, missing='none'):
super(TimeSeriesModel, self).__init__(endog, exog, missing=missing)
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