Covariance Functions

Constant(c)	Constant valued covariance function.
WhiteNoise(sigma)	White noise covariance function.
ExpQuad(input_dim[, ls, ls_inv, active_dims])	The Exponentiated Quadratic kernel.
RatQuad(input_dim, alpha[, ls, ls_inv, ...])	The Rational Quadratic kernel.
Exponential(input_dim[, ls, ls_inv, active_dims])	The Exponential kernel.
Matern52(input_dim[, ls, ls_inv, active_dims])	The Matern kernel with nu = 5/2.
Matern32(input_dim[, ls, ls_inv, active_dims])	The Matern kernel with nu = 3/2.
Linear(input_dim, c[, active_dims])	The Linear kernel.
Polynomial(input_dim, c, d, offset[, ...])	The Polynomial kernel.
Cosine(input_dim[, ls, ls_inv, active_dims])	The Cosine kernel.
Periodic(input_dim, period[, ls, ls_inv, ...])	The Periodic kernel.
WarpedInput(input_dim, cov_func, warp_func)	Warp the inputs of any kernel using an arbitrary function defined using PyTensor.
Gibbs(input_dim, lengthscale_func[, args, ...])	The Gibbs kernel.
Coregion(input_dim[, W, kappa, B, active_dims])	Covariance function for intrinsic/linear coregionalization models.
ScaledCov(input_dim, cov_func, scaling_func)	Construct a kernel by multiplying a base kernel with a scaling function defined using PyTensor.
Kron(factor_list)	Form a covariance object that is the kronecker product of other covariances.