Predicted R-Squared (r2, r^2) Calculation in `python`

stats.py

def press_statistic(y_true, y_pred, xs):
    """
    Calculation of the `Press Statistics <https://www.otexts.org/1580>`_
    """
    res = y_pred - y_true
    hat = xs.dot(np.linalg.pinv(xs))
    den = (1 - np.diagonal(hat))
    sqr = np.square(res/den)
    return sqr.sum()

def predicted_r2(y_true, y_pred, xs):
    """
    Calculation of the `Predicted R-squared <https://rpubs.com/RatherBit/102428>`_
    """
    press = press_statistic(y_true=y_true,
                            y_pred=y_pred,
                            xs=xs
    )

    sst  = np.square( y_true - y_true.mean() ).sum()
    return 1 - press / sst
 
def r2(y_true, y_pred):
    """
    Calculation of the unadjusted r-squared, goodness of fit metric
    """
    sse  = np.square( y_pred - y_true ).sum()
    sst  = np.square( y_true - y_true.mean() ).sum()
    return 1 - sse/sst