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Fix MissingDataError in multi_mra when features contain NaN #350

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Fix MissingDataError in multi_mra when features contain NaN #350

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bc86b90
Fix MissingDataError in multi_mra when features contain NaN
Jun 6, 2026
0f1bd6c
Fix MissingDataError in multi_mra: handle inf and all-NaN columns
Jun 6, 2026
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14 changes: 14 additions & 0 deletions openavmkit/modeling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2039,6 +2039,20 @@ def _run_multi_mra(

has_const = "const" in X_train

# Impute NaN/inf with training-set column medians and propagate to all splits.
# Real-world property data routinely has missing values (parking spaces,
# garage counts, etc.) and derived features can produce inf (e.g. FAR when
# land_area=0). statsmodels OLS raises MissingDataError on any NaN or inf
# in exog, so we replace inf→NaN first, then median-impute. Columns that
# are entirely NaN (no finite training values) fall back to 0.
# This is the same guard pattern used in utilities/stats.py.
X_train = X_train.replace([np.inf, -np.inf], np.nan)
col_medians = X_train.median().fillna(0.0)
X_train = X_train.fillna(col_medians)
ds_prepped.X_test = ds_prepped.X_test.replace([np.inf, -np.inf], np.nan).fillna(col_medians)
ds_prepped.X_sales = ds_prepped.X_sales.replace([np.inf, -np.inf], np.nan).fillna(col_medians)
ds_prepped.X_univ = ds_prepped.X_univ.replace([np.inf, -np.inf], np.nan).fillna(col_medians)

# ------------------------
# Global OLS (fallback)
# ------------------------
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