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