def summary(self) -> Summary:
"""
Summary of both the STL decomposition and the model fit.
Returns
-------
Summary
The summary of the model fit and the STL decomposition.
Notes
-----
Requires that the model's result class supports ``summary`` and
returns a ``Summary`` object.
"""
if not hasattr(self._model_result, "summary"):
raise AttributeError(
"The model result does not have a summary attribute."
)
summary: Summary = self._model_result.summary()
if not isinstance(summary, Summary):
raise TypeError(
"The model result's summary is not a Summary object."
)
summary.tables[0].title = (
"STL Decomposition and " + summary.tables[0].title
)
config = self._stl.config
left_keys = ("period", "seasonal", "robust")
left_data = []
left_stubs = []
right_data = []
right_stubs = []
for key in config:
new = key.capitalize()
new = new.replace("_", " ")
if new in ("Trend", "Low Pass"):
new += " Length"
is_left = any(key.startswith(val) for val in left_keys)
new += ":"
stub = f"{new:<23s}"
val = f"{str(config[key]):>13s}"
if is_left:
left_stubs.append(stub)
left_data.append([val])
else:
right_stubs.append(" " * 6 + stub)
right_data.append([val])
tab = SimpleTable(
left_data, stubs=tuple(left_stubs), title="STL Configuration"
)
tab.extend_right(SimpleTable(right_data, stubs=right_stubs))
summary.tables.append(tab)
return summary
def summary(self):
"""Model summary"""
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)),
('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 eqlabel in self.equation_labels:
results = self.equations[eqlabel]
dep_name = results.dependent
title = 'Equation: {0}, Dependent Variable: {1}'.format(eqlabel, dep_name)
smry.tables.append(param_table(results, title, pad_bottom=True))
return smry
def summary(self):
"""Equation summary"""
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))
return smry
def summary(self):
""":obj:`statsmodels.iolib.summary.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):
""":obj:`statsmodels.iolib.summary.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 = []
extra_text.append('Endogenous: ' + ', '.join(endog))
extra_text.append('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):
""":obj:`statsmodels.iolib.summary.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)),
('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
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):
""":obj:`statsmodels.iolib.summary.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.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
def summary(self):
"""Summary table of model estimation results"""
title = self._method + ' Estimation Summary'
mod = self.model
top_left = [('Dep. Variable:', mod.dependent.cols[0]),
('Estimator:', self._method),
('No. Observations:', self.nobs),
('Date:', self._datetime.strftime('%a, %b %d %Y')),
('Time:', self._datetime.strftime('%H:%M:%S')),
('Cov. Estimator:', self._cov_type), ('', '')]
top_right = [('R-squared:', _str(self.rsquared)),
('Adj. R-squared:', _str(self.rsquared_adj)),
('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] = '%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 = 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 = [
'Parameters', '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)
instruments = self.model.instruments
if instruments.shape[1] > 0:
extra_text = []
endog = self.model.endog
extra_text.append('Endogenous: ' + ', '.join(endog.cols))
extra_text.append('Instruments: ' + ', '.join(instruments.cols))
cov_descr = str(self._cov_estimator)
for line in cov_descr.split('\n'):
extra_text.append(line)
smry.add_extra_txt(extra_text)
return smry
