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 = super(PanelEffectsResults, self).summary
is_invalid = np.isfinite(self.f_pooled.stat)
f_pool = _str(self.f_pooled.stat) if is_invalid else "--"
f_pool_pval = pval_format(self.f_pooled.pval) if is_invalid else "--"
f_pool_name = self.f_pooled.dist_name if is_invalid else "--"
extra_text = []
if is_invalid:
extra_text.append("F-test for Poolability: {0}".format(f_pool))
extra_text.append("P-value: {0}".format(f_pool_pval))
extra_text.append("Distribution: {0}".format(f_pool_name))
extra_text.append("")
if self.included_effects:
effects = ", ".join(self.included_effects)
extra_text.append("Included effects: " + effects)
if self.other_info is not None:
nrow = self.other_info.shape[0]
plural = "s" if nrow > 1 else ""
extra_text.append(f"Model includes {nrow} other effect{plural}")
for c in self.other_info.T:
col = self.other_info.T[c]
extra_text.append("Other Effect {0}:".format(c))
stats = "Avg Obs: {0}, Min Obs: {1}, Max Obs: {2}, Groups: {3}"
stats = stats.format(
_str(col["mean"]),
_str(col["min"]),
_str(col["max"]),
int(col["total"]),
)
extra_text.append(stats)
smry.add_extra_txt(extra_text)
return smry
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
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()``.
"""
title = self.name + " Estimation Summary"
mod = self.model
top_left = [
("Dep. Variable:", mod.dependent.vars[0]),
("Estimator:", self.name),
("No. Observations:", self.nobs),
("Date:", self._datetime.strftime("%a, %b %d %Y")),
("Time:", self._datetime.strftime("%H:%M:%S")),
("Cov. Estimator:", self._cov_type),
("", ""),
("Entities:", str(int(self.entity_info["total"]))),
("Avg Obs:", _str(self.entity_info["mean"])),
("Min Obs:", _str(self.entity_info["min"])),
("Max Obs:", _str(self.entity_info["max"])),
("", ""),
("Time periods:", str(int(self.time_info["total"]))),
("Avg Obs:", _str(self.time_info["mean"])),
("Min Obs:", _str(self.time_info["min"])),
("Max Obs:", _str(self.time_info["max"])),
("", ""),
]
is_invalid = np.isfinite(self.f_statistic.stat)
f_stat = _str(self.f_statistic.stat) if is_invalid else "--"
f_pval = pval_format(self.f_statistic.pval) if is_invalid else "--"
f_dist = self.f_statistic.dist_name if is_invalid else "--"
f_robust = _str(self.f_statistic_robust.stat) if is_invalid else "--"
f_robust_pval = (pval_format(self.f_statistic_robust.pval)
if is_invalid else "--")
f_robust_name = self.f_statistic_robust.dist_name if is_invalid else "--"
top_right = [
("R-squared:", _str(self.rsquared)),
("R-squared (Between):", _str(self.rsquared_between)),
("R-squared (Within):", _str(self.rsquared_within)),
("R-squared (Overall):", _str(self.rsquared_overall)),
("Log-likelihood", _str(self._loglik)),
("", ""),
("F-statistic:", f_stat),
("P-value", f_pval),
("Distribution:", f_dist),
("", ""),
("F-statistic (robust):", f_robust),
("P-value", f_robust_pval),
("Distribution:", f_robust_name),
("", ""),
("", ""),
("", ""),
("", ""),
]
stubs = []
vals = []
for stub, val in top_left:
stubs.append(stub)
vals.append([val])
table = SimpleTable(vals, txt_fmt=fmt_2cols, title=title, stubs=stubs)
# create summary table instance
smry = Summary()
# Top Table
# Parameter table
fmt = fmt_2cols
fmt["data_fmts"][1] = "%18s"
top_right = [("%-21s" % (" " + k), v) for k, v in top_right]
stubs = []
vals = []
for stub, val in top_right:
stubs.append(stub)
vals.append([val])
table.extend_right(SimpleTable(vals, stubs=stubs))
smry.tables.append(table)
param_data = np.c_[self.params.values[:, None],
self.std_errors.values[:, None],
self.tstats.values[:,
None], self.pvalues.values[:,
None],
self.conf_int(), ]
data = []
for row in param_data:
txt_row = []
for i, v in enumerate(row):
f = _str
if i == 3:
f = pval_format
txt_row.append(f(v))
data.append(txt_row)
title = "Parameter Estimates"
table_stubs = list(self.params.index)
header = [
"Parameter", "Std. Err.", "T-stat", "P-value", "Lower CI",
"Upper CI"
]
table = SimpleTable(data,
stubs=table_stubs,
txt_fmt=fmt_params,
headers=header,
title=title)
smry.tables.append(table)
return smry
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()``.
"""
title = self.name + " Estimation Summary"
top_left = [
("No. Test Portfolios:", len(self._portfolio_names)),
("No. Factors:", len(self._factor_names)),
("No. Observations:", self.nobs),
("Date:", self._datetime.strftime("%a, %b %d %Y")),
("Time:", self._datetime.strftime("%H:%M:%S")),
("Cov. Estimator:", self._cov_type),
("", ""),
]
j_stat = _str(self.j_statistic.stat)
j_pval = pval_format(self.j_statistic.pval)
j_dist = self.j_statistic.dist_name
top_right = [
("R-squared:", _str(self.rsquared)),
("J-statistic:", j_stat),
("P-value", j_pval),
("Distribution:", j_dist),
("", ""),
("", ""),
("", ""),
]
stubs = []
vals = []
for stub, val in top_left:
stubs.append(stub)
vals.append([val])
table = SimpleTable(vals, txt_fmt=fmt_2cols, title=title, stubs=stubs)
# create summary table instance
smry = Summary()
# Top Table
# Parameter table
fmt = fmt_2cols
fmt["data_fmts"][1] = "%18s"
top_right = [("%-21s" % (" " + k), v) for k, v in top_right]
stubs = []
vals = []
for stub, val in top_right:
stubs.append(stub)
vals.append([val])
table.extend_right(SimpleTable(vals, stubs=stubs))
smry.tables.append(table)
rp = np.asarray(self.risk_premia)[:, None]
se = np.asarray(self.risk_premia_se)[:, None]
tstats = np.asarray(self.risk_premia / self.risk_premia_se)
pvalues = 2 - 2 * stats.norm.cdf(np.abs(tstats))
ci = rp + se * stats.norm.ppf([[0.025, 0.975]])
param_data = np.c_[rp, se, tstats[:, None], pvalues[:, None], ci]
data = []
for row in param_data:
txt_row = []
for i, v in enumerate(row):
f = _str
if i == 3:
f = pval_format
txt_row.append(f(v))
data.append(txt_row)
title = "Risk Premia Estimates"
table_stubs = list(self.risk_premia.index)
header = ["Parameter", "Std. Err.", "T-stat", "P-value", "Lower CI", "Upper CI"]
table = SimpleTable(
data, stubs=table_stubs, txt_fmt=fmt_params, headers=header, title=title
)
smry.tables.append(table)
smry.add_extra_txt(
[
"Covariance estimator:",
str(self._cov_est),
"See full_summary for complete results",
]
)
return smry
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()``.
"""
title = self._method + " Estimation Summary"
top_left = [
("Eq. Label:", self.equation_label),
("Dep. Variable:", self.dependent),
("Estimator:", self._method),
("No. Observations:", self.nobs),
("Date:", self._datetime.strftime("%a, %b %d %Y")),
("Time:", self._datetime.strftime("%H:%M:%S")),
("", ""),
]
top_right = [
("R-squared:", _str(self.rsquared)),
("Adj. R-squared:", _str(self.rsquared_adj)),
("Cov. Estimator:", self._cov_type),
("F-statistic:", _str(self.f_statistic.stat)),
("P-value (F-stat)", pval_format(self.f_statistic.pval)),
("Distribution:", str(self.f_statistic.dist_name)),
("", ""),
]
stubs = []
vals = []
for stub, val in top_left:
stubs.append(stub)
vals.append([val])
table = SimpleTable(vals, txt_fmt=fmt_2cols, title=title, stubs=stubs)
# create summary table instance
smry = Summary()
# Top Table
# Parameter table
fmt = fmt_2cols
fmt["data_fmts"][1] = "%10s"
top_right = [("%-21s" % (" " + k), v) for k, v in top_right]
stubs = []
vals = []
for stub, val in top_right:
stubs.append(stub)
vals.append([val])
table.extend_right(SimpleTable(vals, stubs=stubs))
smry.tables.append(table)
smry.tables.append(
param_table(self, "Parameter Estimates", pad_bottom=True))
extra_text = []
instruments = self._instruments
if instruments:
endog = self._endog
extra_text = [
"Endogenous: " + ", ".join(endog),
"Instruments: " + ", ".join(instruments),
]
extra_text.append("Covariance Estimator:")
for line in str(self._cov_estimator).split("\n"):
extra_text.append(line)
if self._weight_estimator:
extra_text.append("Weight Estimator:")
for line in str(self._weight_estimator).split("\n"):
extra_text.append(line)
smry.add_extra_txt(extra_text)
return smry
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()``.
"""
title = "System " + self._method + " Estimation Summary"
top_left = [
("Estimator:", self._method),
("No. Equations.:", str(len(self.equation_labels))),
("No. Observations:", str(self.resids.shape[0])),
("Date:", self._datetime.strftime("%a, %b %d %Y")),
("Time:", self._datetime.strftime("%H:%M:%S")),
("", ""),
("", ""),
]
top_right = [
("Overall R-squared:", _str(self.rsquared)),
("McElroy's R-squared:", _str(self.system_rsquared.mcelroy)),
("Judge's (OLS) R-squared:", _str(self.system_rsquared.judge)),
("Berndt's R-squared:", _str(self.system_rsquared.berndt)),
("Dhrymes's R-squared:", _str(self.system_rsquared.dhrymes)),
("Cov. Estimator:", self._cov_type),
("Num. Constraints: ", self._num_constraints),
]
stubs = []
vals = []
for stub, val in top_left:
stubs.append(stub)
vals.append([val])
table = SimpleTable(vals, txt_fmt=fmt_2cols, title=title, stubs=stubs)
# create summary table instance
smry = Summary()
# Top Table
# Parameter table
fmt = fmt_2cols
fmt["data_fmts"][1] = "%10s"
top_right = [("%-21s" % (" " + k), v) for k, v in top_right]
stubs = []
vals = []
for stub, val in top_right:
stubs.append(stub)
vals.append([val])
table.extend_right(SimpleTable(vals, stubs=stubs))
smry.tables.append(table)
for i, eqlabel in enumerate(self.equation_labels):
last_row = i == (len(self.equation_labels) - 1)
results = self.equations[eqlabel]
dep_name = results.dependent
title = "Equation: {0}, Dependent Variable: {1}".format(
eqlabel, dep_name)
pad_bottom = results.instruments is not None and not last_row
smry.tables.append(
param_table(results, title, pad_bottom=pad_bottom))
if results.instruments:
formatted = format_wide(results.instruments, 80)
if not last_row:
formatted.append([" "])
smry.tables.append(
SimpleTable(formatted, headers=["Instruments"]))
extra_text = ["Covariance Estimator:"]
for line in str(self._cov_estimator).split("\n"):
extra_text.append(line)
if self._weight_estimtor:
extra_text.append("Weight Estimator:")
for line in str(self._weight_estimtor).split("\n"):
extra_text.append(line)
smry.add_extra_txt(extra_text)
return smry
