nispace.stats.coloc.ridge

nispace.stats.coloc.ridge(x, y, cv=None, seed=None, kwargs={})[source]

Ridge-regularized regression of x on y via sklearn.linear_model.RidgeCV.

Parameters:

  • x (np.ndarray, shape (n_obs, n_predictors)) – Does not handle NaN – sklearn errors on NaN input; pre-mask.

  • y (np.ndarray, shape (n_obs,)) –

  • cv (int, cross-validation generator, or None) – Passed to RidgeCV for selecting alpha.

  • seed (int, optional) – Unused by RidgeCV (which has no random_state); accepted for a uniform signature with lasso/elasticnet.

  • kwargs (dict, default {}) – Forwarded to RidgeCV.

Returns:

out – "alpha" (selected regularization strength), "r2", "beta" (shape (n_predictors,)).

Return type:

dict

Notes

Used by core/colocalize.py’s regularized-regression colocalization case, with NaN excluded list-wise (see elasticnet’s Notes) before calling this function.