def __init__( self, x: List[ndarray], eps: NDArray, sigma: NDArray, full_sigma: NDArray, *, gls: bool = False, debiased: bool = False, constraints: Optional[LinearConstraint] = None, kernel: str = "bartlett", bandwidth: Optional[float] = None, ): _HACMixin.__init__(self, kernel, bandwidth) super(KernelCovariance, self).__init__( x, eps, sigma, full_sigma, gls=gls, debiased=debiased, constraints=constraints, ) self._check_kernel(kernel) self._check_bandwidth(bandwidth) self._name = "Kernel (HAC) Covariance" self._str_extra["Kernel"] = kernel self._cov_config["kernel"] = kernel
def __init__( self, x: List[ndarray], z: List[ndarray], eps: NDArray, w: NDArray, *, sigma: Optional[ndarray] = None, debiased: bool = False, constraints: Optional[LinearConstraint] = None, kernel: str = "bartlett", bandwidth: Optional[float] = None, ) -> None: _HACMixin.__init__(self, kernel, bandwidth) super().__init__(x, z, eps, w, sigma=sigma, debiased=debiased, constraints=constraints) self._name = "GMM Kernel (HAC) Covariance" self._check_bandwidth(bandwidth) self._check_kernel(kernel) self._cov_config["kernel"] = kernel
def __init__( self, center: bool = False, debiased: bool = False, kernel: str = "bartlett", bandwidth: Optional[float] = None, optimal_bw: bool = False, ) -> None: _HACMixin.__init__(self, kernel, bandwidth) super(KernelWeightMatrix, self).__init__(center, debiased) self._name = "Kernel (HAC) Weighting" self._check_kernel(kernel) self._check_bandwidth(bandwidth) self._predefined_bw = self._bandwidth self._optimal_bw = optimal_bw