def __init__()

in svinfer/linear_model/linear_regression.py [0:0]

• 17 lines of code
• 5 McCabe index (conditional complexity)

    def __init__(self, n, xtx, xty, yty, x_s2, df_corrected=True):
        if xtx.shape[0] != xtx.shape[1]:
            raise ValueError("xtx should be square matrix!")
        if xtx.shape[0] != xty.shape[0]:
            raise ValueError("xtx and xty have unmatched dimension")
        if any(s2 < 0.0 for s2 in x_s2):
            raise ValueError("x_s2 should not contain negative elements")
        self.n = n
        self.xtx = xtx
        self.xty = xty
        self.yty = yty
        self.x_s2 = x_s2
        self.df_corrected = df_corrected
        self.k = self.xtx.shape[0]
        self.beta = None
        self.sigma_sq = None
        self.omega = None