diff --git a/README.md b/README.md index 8039974..9c190ca 100644 --- a/README.md +++ b/README.md @@ -23,6 +23,7 @@ The package supports multiple output formats including: - [PyFixest](https://github.com/py-econometrics/pyfixest) - [statsmodels](https://github.com/statsmodels/statsmodels) - [linearmodels](https://github.com/bashtage/linearmodels) +- [glum](https://github.com/Quantco/glum) ## Origin diff --git a/docs/SupportedModelClasses.md b/docs/SupportedModelClasses.md index 3b62538..68e2573 100644 --- a/docs/SupportedModelClasses.md +++ b/docs/SupportedModelClasses.md @@ -1,7 +1,8 @@ # Supported Model Classes -`maketables` supports creating regression tables for models from the following packages: +`maketables` supports creating regression tables for models from the following packages: - [PyFixest](https://github.com/py-econometrics/pyfixest) - [statsmodels](https://github.com/statsmodels/statsmodels) -- [linearmodels](https://github.com/bashtage/linearmodels) \ No newline at end of file +- [linearmodels](https://github.com/bashtage/linearmodels) +- [glum](https://github.com/Quantco/glum) \ No newline at end of file diff --git a/maketables/extractors.py b/maketables/extractors.py index 93d0079..6f05481 100644 --- a/maketables/extractors.py +++ b/maketables/extractors.py @@ -34,6 +34,13 @@ HAS_LINEARMODELS = False PanelOLSResults = RandomEffectsResults = IV2SLSResults = IVGMMResults = () # type: ignore +try: + from glum import GeneralizedLinearRegressor, GeneralizedLinearRegressorCV + HAS_GLUM = True +except Exception: + HAS_GLUM = False + GeneralizedLinearRegressor = GeneralizedLinearRegressorCV = () # type: ignore + @runtime_checkable class ModelExtractor(Protocol): @@ -715,8 +722,130 @@ def supported_stats(self, model: Any) -> set[str]: k for k, spec in self.STAT_MAP.items() if _get_attr(model, spec) is not None } + +class GlumExtractor: + """ + Extractor for glum regression results. + + Handles GeneralizedLinearRegressor and GeneralizedLinearRegressorCV from glum. + GLUM shares the same API as statsmodels for fitted model results. + """ + + def can_handle(self, model: Any) -> bool: + """Check if model is a glum fitted result.""" + if GeneralizedLinearRegressor == (): + return False + try: + return isinstance(model, (GeneralizedLinearRegressor, GeneralizedLinearRegressorCV)) + except Exception: + return False + + def coef_table(self, model: Any) -> pd.DataFrame: + """ + Extract coefficient table from glum result. + + Constructs standardized DataFrame from params, bse, pvalues, and + optionally tvalues attributes of the glum result. + + Returns + ------- + DataFrame with columns: Estimate, Std. Error, Pr(>|t|), and optionally t value. + """ + + coef_table = model.coef_table() + if isinstance(coef_table, pd.Series): + # no inference stored / computed + k = len(coef_table) + coef = coef_table + se = pd.Series(['n.c.'] * k) + t_value = pd.Series(['n.c.'] * k) + p_value = pd.Series(['n.c.'] * k) + else: + coef = coef_table.coef + se = coef_table.se + t_value = coef_table.t_value + p_value = coef_table.p_value + #ci_lower = coef_table.ci_lower + #ci_upper = coef_table.ci_upper + + df = pd.DataFrame({ + "Estimate": coef, + "Std. Error": se, + "Pr(>|t|)": p_value, + "t value": t_value + }) + + return df + + + def depvar(self, model: Any) -> str: + """ + Try to extract dependent variable from formula attribute. + + Returns + ------- + Dependent variable name or "y" if not found. + """ + + formula = getattr(model, 'formula', None) + if formula and isinstance(formula, str) and '~' in formula: + return formula.split('~')[0].strip() + return "y" + + def fixef_string(self, model: Any) -> str | None: + """ + GLUM does not sweep out fixed effects during estimation and therefore + fixed effects are (efficiently) estimated as 'regular' coefficients. + """ + return None + + # Unified stat keys -> glum attributes/callables + STAT_MAP: ClassVar[dict[str, Any]] = { + "N": "_num_obs", + "n_iter": "n_iter_", + "family": "family", + "link": "link", + "se_type": lambda m: "robust" if getattr(m, "robust", None) is True else ("iid" if getattr(m, "robust", None) is False else None), + } + + def stat(self, model: Any, key: str) -> Any: + """Extract a specific statistic from a glum fitted model.""" + spec = self.STAT_MAP.get(key) + if spec is None: + return None + val = _get_attr(model, spec) + if key == "N" and val is not None: + try: + return int(val) + except Exception: + return val + return val + + def vcov_info(self, model: Any) -> dict[str, Any]: + """Extract variance-covariance information from a glum fitted model.""" + robust = getattr(model, "robust", None) + if robust is True: + vcov_type = "robust" + elif robust is False: + vcov_type = "iid" + else: + vcov_type = None + return {"vcov_type": vcov_type, "clustervar": None} + + def var_labels(self, model: Any) -> dict[str, str] | None: + """Extract variable labels from a glum fitted model.""" + pass + + def supported_stats(self, model: Any) -> set[str]: + """Return set of statistics available for the given glum model.""" + return { + k for k, spec in self.STAT_MAP.items() if _get_attr(model, spec) is not None + } + + # Register built-ins clear_extractors() register_extractor(PyFixestExtractor()) register_extractor(LinearmodelsExtractor()) +register_extractor(GlumExtractor()) register_extractor(StatsmodelsExtractor()) diff --git a/pixi.lock b/pixi.lock index c25a993..e2d23b7 100644 --- a/pixi.lock +++ b/pixi.lock @@ -1187,6 +1187,539 @@ environments: - 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