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()``. """ 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" 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._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