Gaussian Process Log-Density (Squared Exponential Kernel)

Calculates the log-density of a Gaussian Process with a Squared Exponential (RBF) kernel.

Usage

gaussian_process_lpdf(
  y,
  x,
  mean = 0,
  magnitude = 1,
  smoothing = 1,
  noise = 0.01,
  sum = TRUE
)

Arguments

y

Observation vector (N), or matrix (M x N) whose rows are independent GP realizations on the same coordinates.

x

Coordinate vector or matrix (N x D), where N matches length(y) for vector y or ncol(y) for matrix y.

mean

Mean vector (scalar, length N, or M x N matrix for matrix y).

magnitude

Signal standard deviation (alpha).

smoothing

Length-scale (rho).

noise

Measurement noise standard deviation (sigma).

sum

Logical; whether to return the sum of log-densities. If FALSE and y is a matrix, returns one log-density per row.

Value

Log-density value.