def test_add_star(pvalue):
if pvalue <= 0.01:
expected = "***"
elif pvalue <= 0.05:
expected = "**"
elif pvalue <= 0.10:
expected = "*"
else:
expected = ""
result = add_star("", pvalue, True)
assert expected == result
def summary(self) -> Summary:
"""
Model estimation summary.
Returns
-------
Summary
Summary table of model estimation results
Supports export to csv, html and latex using the methods ``summary.as_csv()``,
``summary.as_html()`` and ``summary.as_latex()``.
"""
smry = Summary()
models = list(self._results.keys())
title = "Model Comparison"
stubs = [
"Dep. Variable",
"Estimator",
"No. Observations",
"Cov. Est.",
"R-squared",
"R-Squared (Within)",
"R-Squared (Between)",
"R-Squared (Overall)",
"F-statistic",
"P-value (F-stat)",
]
dep_name = {}
for key in self._results:
dep_name[key] = self._results[key].model.dependent.vars[0]
dep_name = Series(dep_name)
vals = concat(
[
dep_name,
self.estimator_method,
self.nobs,
self.cov_estimator,
self.rsquared,
self.rsquared_within,
self.rsquared_between,
self.rsquared_overall,
self.f_statistic,
],
axis=1,
)
vals = [[i for i in v] for v in vals.T.values]
vals[2] = [str(v) for v in vals[2]]
for i in range(4, len(vals)):
f = _str
if i == 9:
f = pval_format
vals[i] = [f(v) for v in vals[i]]
params = self.params
precision = getattr(self, self._precision)
pvalues = np.asarray(self.pvalues)
params_fmt = []
params_stub = []
for i in range(len(params)):
formatted_and_starred = []
for v, pv in zip(params.values[i], pvalues[i]):
formatted_and_starred.append(add_star(_str(v), pv,
self._stars))
params_fmt.append(formatted_and_starred)
precision_fmt = []
for v in precision.values[i]:
v_str = _str(v)
v_str = "({0})".format(v_str) if v_str.strip() else v_str
precision_fmt.append(v_str)
params_fmt.append(precision_fmt)
params_stub.append(params.index[i])
params_stub.append(" ")
vals = table_concat((vals, params_fmt))
stubs = stub_concat((stubs, params_stub))
all_effects = []
for key in self._results:
res = self._results[key]
effects = getattr(res, "included_effects", [])
all_effects.append(effects)
neffect = max(map(len, all_effects))
effects = []
effects_stub = ["Effects"]
for i in range(neffect):
if i > 0:
effects_stub.append("")
row = []
for j in range(len(self._results)):
effect = all_effects[j]
if len(effect) > i:
row.append(effect[i])
else:
row.append("")
effects.append(row)
if effects:
vals = table_concat((vals, effects))
stubs = stub_concat((stubs, effects_stub))
txt_fmt = default_txt_fmt.copy()
txt_fmt["data_aligns"] = "r"
txt_fmt["header_align"] = "r"
table = SimpleTable(vals,
headers=models,
title=title,
stubs=stubs,
txt_fmt=txt_fmt)
smry.tables.append(table)
prec_type = self._PRECISION_TYPES[self._precision]
smry.add_extra_txt(["{0} reported in parentheses".format(prec_type)])
return smry