# Covariance Functions#

 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.