class TestGLMPoissonCluFit(CheckCountRobustMixin):
res2 = results_st.results_poisson_clu
cov_type = 'cluster'
model_cls = GLM
mod_kwargs = {"family": families.Poisson()}
cov_kwds = dict(groups=group, use_correction=True,
df_correction=True) # TODO has no effect
fit_kwargs = {
"cov_type": cov_type,
"cov_kwds": cov_kwds,
"use_t": False
} # True,
@classmethod
def setup_class(cls):
mod = cls.model_cls(endog, exog, **cls.mod_kwargs)
cls.res1 = mod.fit(disp=False, **cls.fit_kwargs)
# The model results, t_test, ... should also work without
# normalized_cov_params, see GH#2209
# Note: we cannot set on the wrapper res1, we need res1._results
cls.res1._results.normalized_cov_params = None
cls.bse_rob = cls.res1.bse
cls.get_corr_fact()
class TestGLMPoissonClu(CheckCountRobustMixin):
res2 = results_st.results_poisson_clu
model_cls = GLM
mod_kwargs = {"family": families.Poisson()}
@classmethod
def setup_class(cls):
mod = cls.model_cls(endog, exog, **cls.mod_kwargs)
cls.res1 = mod.fit(disp=False, **cls.fit_kwargs)
cls.get_robust_clu()
class TestGLMPoissonHC1Generic(CheckCountRobustMixin):
res2 = results_st.results_poisson_hc1
model_cls = GLM
mod_kwargs = {"family": families.Poisson()}
@classmethod
def setup_class(cls):
mod = cls.model_cls(endog, exog, **cls.mod_kwargs)
cls.res1 = mod.fit(disp=False, **cls.fit_kwargs)
get_robustcov_results(cls.res1._results, 'HC1', use_self=True)
cls.bse_rob = cls.res1.bse
cls.get_corr_fact(use_k=False)
class TestGLMPoissonHC1Fit(CheckCountRobustMixin):
res2 = results_st.results_poisson_hc1
cov_type = 'HC1'
model_cls = GLM
mod_kwargs = {"family": families.Poisson()}
fit_kwargs = {"cov_type": cov_type}
@classmethod
def setup_class(cls):
mod = cls.model_cls(endog, exog, **cls.mod_kwargs)
cls.res1 = mod.fit(disp=False, **cls.fit_kwargs)
cls.bse_rob = cls.res1.bse
cls.get_corr_fact(use_k=False)
class TestGLMPoissonCluGeneric(CheckCountRobustMixin):
res2 = results_st.results_poisson_clu
cov_type = 'cluster'
model_cls = GLM
mod_kwargs = {"family": families.Poisson()}
@classmethod
def setup_class(cls):
mod = cls.model_cls(endog, exog, **cls.mod_kwargs)
cls.res1 = mod.fit(disp=False, **cls.fit_kwargs)
get_robustcov_results(
cls.res1._results,
cls.cov_type,
groups=group,
use_correction=True,
df_correction=True, # TODO has no effect
use_t=False, # True,
use_self=True)
cls.bse_rob = cls.res1.bse
cls.get_corr_fact()