WhiteNoiseKernel

class pmrf.covariance_kernels.WhiteNoiseKernel(variance: Array | ndarray | bool | number | bool | int | float | complex)

Bases: AbstractCovarianceKernel

Kernel representing independent Gaussian noise.

Parameters:: variance (ArrayLike) – Noise variance level.

__call__(x1, x2, key=None)

Evaluate the kernel between two points.

Parameters:

x1 (jnp.ndarray) – First input point.
x2 (jnp.ndarray) – Second input point.
key (jax.random.PRNGKey, optional) – Random key for stochastic kernels.

Returns:

Kernel covariance scalar.

Return type:

jnp.ndarray

variance: Array | ndarray | bool | number | bool | int | float | complex: The variance.