adds plan + rules

Author: Dpananos

.cursor/plans/glm-fixed-effects-support-5e7c976a.plan.md

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+<!-- 5e7c976a-5d57-4559-9eec-e537dca963a1 9818a1cd-a593-4f12-a9f7-6caba18c5fcb -->
+# Add Fixed Effects Support to feglm (Gaussian Family)
+
+## Current State
+
+The `Feglm` class (in `feglm_.py`) currently raises `NotImplementedError` at line 99-100 when fixed effects are present. However, the infrastructure is largely in place:
+
+- The `residualize()` method exists (lines 304-323) and correctly calls `demean()`
+- Fixed effects are already handled in `prepare_model_matrix()` and `to_array()` methods
+- Separation checks (lines 102-126) are already conditional on `self._fe is not None`
+
+The `Fepois` class successfully implements fixed effects in its IRLS algorithm (lines 282-294 in `fepois_.py`) by calling `demean()` with fixed effects and weights at each iteration.
+
+## Implementation Steps
+
+### 1. Remove Fixed Effects Restriction in feglm_.py
+
+Remove the restriction in `prepare_model_matrix()` method:
+
+- Delete lines 99-100 that raise `NotImplementedError` for fixed effects
+- This will allow the rest of the code to execute when fixed effects are present
+
+### 2. Verify residualize() Method Integration
+
+The `residualize()` method (lines 304-323) already properly handles fixed effects:
+
+- Returns unchanged data when `flist is None` (no fixed effects)
+- Calls `demean()` with weights when fixed effects exist
+- This method is already called in `get_fit()` at line 182
+
+The implementation should work as-is since:
+
+- `Fegaussian` inherits from `Feglm`
+- The IRLS algorithm in `get_fit()` calls `residualize()` at each iteration (line 182)
+- Weights are properly passed as `W_tilde.flatten()` (line 186)
+
+### 3. Test the Implementation
+
+Enable and extend existing tests:
+
+**a) Enable skipped test in `test_feols_feglm_internally.py`:**
+
+- Remove the `@pytest.mark.skip` decorator on line 60
+- Run the test to verify it passes with the implementation
+
+**b) Add basic R comparison tests:**
+
+- Add tests to `test_vs_fixest.py` comparing `pf.feglm(family="gaussian")` against R's `fixest::feglm(family="gaussian")`
+- Test formulas: `"Y ~ X1 | f1"`, `"Y ~ X1 | f1 + f2"`, `"Y ~ X1 + X2 | f2"`
+- Compare: coefficients, standard errors, residuals
+- Use existing test patterns from the `glm_fmls` tests (around line 119)
+
+### 4. Validation Checklist
+
+Ensure the implementation correctly handles:
+
+- Single fixed effect: `Y ~ X1 | f1`
+- Multiple fixed effects: `Y ~ X1 | f1 + f2`
+- Fixed effects with multiple covariates: `Y ~ X1 + X2 | f1`
+- Proper weight handling in demeaning at each IRLS iteration
+- Convergence behavior (should still converge in 1 iteration for Gaussian)
+
+## Key Files to Modify
+
+- `pyfixest/estimation/feglm_.py` (remove restriction)
+- `tests/test_feols_feglm_internally.py` (enable skipped test)
+- `tests/test_vs_fixest.py` (add R comparison tests)
+
+## Expected Behavior
+
+After implementation, `pf.feglm(fml="Y ~ X1 | f1", family="gaussian")` should:
+
+1. Accept the formula without raising `NotImplementedError`
+2. Demean variables by fixed effects at each IRLS iteration
+3. Produce identical results to R's `fixest::feglm()` with Gaussian family
+4. For Gaussian family, should effectively match `feols()` results (with appropriate inference adjustments)
+
+### To-dos
+
+- [ ] Remove NotImplementedError for fixed effects in feglm_.py (lines 99-100)
+- [ ] Remove @pytest.mark.skip decorator from test_feols_feglm_internally
+- [ ] Add R comparison tests for Gaussian GLM with fixed effects to test_vs_fixest.py
+- [ ] Run tests and validate against R fixest results

.cursor/rules/pixi.mdc

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+---
+description: Running unit tests
+alwaysApply: false
+---
+When running unit tests, always:
+
+* use pixi to run the test.  We have a dev environement called "dev" that should house all dependencies.
+
+When running unit tests, never:
+
+* Alter the tolerance to get the test to pass.  Use a default tolerance of 1e-06 when comparing two floats.