incubodac

def compute_vif_intercept_ave(model, X, sr):
    """
    Compute average VIF for each predictor group, supporting sparse, numpy, and torch.Tensor X.
    """
    from sklearn.linear_model import LinearRegression
    import numpy as np
    import torch

    vifregr = LinearRegression(n_jobs=-1, fit_intercept=False)  # Correct: no intercept for VIF
    delays_ = np.arange(int(np.round(model.tmin * sr)), int(np.round(model.tmax * sr) + 1))