LuasKernel.K_inv_by_vec#
- LuasKernel.K_inv_by_vec(hp: Any, x_l: Array, x_t: Array, R: Array) Array [source]#
Calculates the product of the inverse of the covariance matrix with a vector, represented by a JAXArray of shape
(N_l, N_t)
. Useful for testing for numerical stability.- Parameters:
hp (Pytree) – Hyperparameters needed to build the covariance matrices
Kl
,Kt
,Sl
,St
. Will be unaffected if additional mean function parameters are also included.x_l (JAXArray) – Array containing wavelength/vertical dimension regression variable(s) for the observed locations. May be of shape
(N_l,)
or(d_l,N_l)
ford_l
different wavelength/vertical regression variables.x_t (JAXArray) – Array containing time/horizontal dimension regression variable(s) for the observed locations. May be of shape
(N_t,)
or(d_t,N_t)
ford_t
different time/horizontal regression variables.R (JAXArray) – JAXArray of shape
(N_l, N_t)
representing the vector to multiply on the right by the inverse of the covariance matrixK
.
- Returns:
The result of multiplying the inverse of the covariance matrix
K
by the vectorR
.- Return type:
JAXArray