def __init__(self, model, params, normalized_cov_params, scale):
super(RLMResults, self).__init__(model, params, normalized_cov_params,
scale)
self.model = model
self.df_model = model.df_model
self.df_resid = model.df_resid
self.nobs = model.nobs
self._cache = resettable_cache()
#for remove_data
self.data_in_cache = ['sresid']
def __init__(self, model, params, normalized_cov_params, scale):
super(RLMResults, self).__init__(model, params,
normalized_cov_params, scale)
self.model = model
self.df_model = model.df_model
self.df_resid = model.df_resid
self.nobs = model.nobs
self._cache = resettable_cache()
#for remove_data
self.data_in_cache = ['sresid']
def __init__(self, model, params, normalized_cov_params, scale):
super(GLMResults, self).__init__(model, params,
normalized_cov_params=normalized_cov_params, scale=scale)
self.family = model.family
self._endog = model.endog
self.nobs = model.endog.shape[0]
self.mu = model.mu
self._data_weights = model.data_weights
self.df_resid = model.df_resid
self.df_model = model.df_model
self.pinv_wexog = model.pinv_wexog
self._cache = resettable_cache()
def __init__(self, model, params, normalized_cov_params, scale):
super(GLMResults,
self).__init__(model,
params,
normalized_cov_params=normalized_cov_params,
scale=scale)
self.family = model.family
self._endog = model.endog
self.nobs = model.endog.shape[0]
self.mu = model.mu
self._data_weights = model.data_weights
self.df_resid = model.df_resid
self.df_model = model.df_model
self.pinv_wexog = model.pinv_wexog
self._cache = resettable_cache()
def __init__(self, model, params, normalized_cov_params=None, scale=1.):
super(ARResults, self).__init__(model, params, normalized_cov_params,
scale)
self._cache = resettable_cache()
self.nobs = model.nobs
n_totobs = len(model.endog)
self.n_totobs = n_totobs
self.X = model.X # copy?
self.Y = model.Y
k_ar = model.k_ar
self.k_ar = k_ar
k_trend = model.k_trend
self.k_trend = k_trend
trendorder = None
if k_trend > 0:
trendorder = k_trend - 1
self.trendorder = 1
#TODO: cmle vs mle?
self.df_resid = self.model.df_resid = n_totobs - k_ar - k_trend
def __init__(self, model, params, normalized_cov_params=None, scale=1.):
super(ARMAResults, self).__init__(model, params, normalized_cov_params,
scale)
self.sigma2 = model.sigma2
nobs = model.nobs
self.nobs = nobs
k_exog = model.k_exog
self.k_exog = k_exog
k_trend = model.k_trend
self.k_trend = k_trend
k_ar = model.k_ar
self.k_ar = k_ar
self.n_totobs = len(model.endog)
k_ma = model.k_ma
self.k_ma = k_ma
df_model = k_exog + k_trend + k_ar + k_ma
self.df_model = df_model
self.df_resid = self.nobs - df_model
self._cache = resettable_cache()
def __init__(self, model, params, normalized_cov_params=None, scale=1.):
super(ARMAResults, self).__init__(model, params, normalized_cov_params,
scale)
self.sigma2 = model.sigma2
nobs = model.nobs
self.nobs = nobs
k_exog = model.k_exog
self.k_exog = k_exog
k_trend = model.k_trend
self.k_trend = k_trend
k_ar = model.k_ar
self.k_ar = k_ar
self.n_totobs = len(model.endog)
k_ma = model.k_ma
self.k_ma = k_ma
df_model = k_exog + k_trend + k_ar + k_ma
self.df_model = df_model
self.df_resid = self.nobs - df_model
self._cache = resettable_cache()
def __init__(self, endog, exog=None, **kwds):
self._orig_endog = endog
self._orig_exog = exog
self.endog, self.exog = self._convert_endog_exog(endog, exog)
self._check_integrity()
self._cache = resettable_cache()
def __init__(self, endog, exog=None, **kwds):
self._orig_endog = endog
self._orig_exog = exog
self.endog, self.exog = self._convert_endog_exog(endog, exog)
self._check_integrity()
self._cache = resettable_cache()
