PeriodicKernel

class pmrf.covariance_kernels.PeriodicKernel(period: Any, lengthscale: Any)

Bases: AbstractCovarianceKernel

Periodic (Exp-Sine-Squared) kernel.

Models functions that repeat over a specific period.

Parameters:

  • period (pmrf.Param) – The period of the kernel, dictating the distance between repetitions.

  • lengthscale (pmrf.Param) – Characteristic length scale of the correlation.

__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

lengthscale: AbstractVariable | Inexact[jaxlib._jax.Array, '...']

The lengthscale,

period: AbstractVariable | Inexact[jaxlib._jax.Array, '...']

The period.