Periodic covariance kernel

Computes a periodic kernel with a shared period and either an isotropic length scale or one ARD length scale per input dimension.

Usage

kernel_periodic(x, y = NULL, variance = 1, length_scale = 1, period = 1)

Arguments

x

Numeric vector or matrix. Matrix rows are observations and columns are input dimensions.

y

Optional numeric vector or matrix with the same number of input dimensions as x. If NULL, computes the covariance of x with itself.

variance

Positive marginal variance.

length_scale

Positive scalar or numeric vector with one value per input dimension. A vector enables ARD.

period

Positive period shared across input dimensions.

Value

A numeric covariance matrix.

Stability

Stable: from version 1.0.0 this interface changes incompatibly only in a major release, after a deprecation period. Results and options that concern an experimental model class, kernel, or argument follow that interface's tier. See gaussianprocesses-package for the policy.

See also

periodic_kernel() creates the same kernel as a reusable specification, which can be combined, optimized, and used in models.

Examples

x <- c(0, 0.25, 1, 2)
covariance <- kernel_periodic(x, length_scale = 0.8, period = 1)

# Inputs a whole number of periods apart are perfectly correlated.
covariance[1, ]
#> [1] 1.0000000 0.2096114 1.0000000 1.0000000