covariance.py 文件源码

def __init__(self, x, eps, sigma, full_sigma, gls=False, debiased=False, constraints=None):
        super(HeteroskedasticCovariance, self).__init__(x, eps, sigma, full_sigma,
                                                        gls=gls,
                                                        debiased=debiased,
                                                        constraints=constraints)
        self._name = 'Heteroskedastic (Robust) Covariance'

        k = len(x)
        weights = inv(sigma) if gls else eye(k)
        bigx = blocked_diag_product(x, weights)
        nobs = eps.shape[0]
        e = eps.T.ravel()[:, None]
        bigxe = bigx * e
        m = bigx.shape[1]
        xe = zeros((nobs, m))
        for i in range(nobs):
            xe[i, :] = bigxe[i::nobs].sum(0)[None, :]
        self._moments = xe