se_kernel: Squared Exponential Kernel

In MagmaClustR: Clustering and Prediction using Multi-Task Gaussian Processes with Common Mean

Squared Exponential Kernel

Description

Squared Exponential Kernel

Usage

se_kernel(x, y, hp, deriv = NULL, vectorized = FALSE)

Arguments

x	A vector (or matrix if vectorized = T) of inputs.
y	A vector (or matrix if vectorized = T) of inputs.
hp	A tibble, data frame or named vector, containing the kernel's hyperparameters. Required columns: 'se_variance', 'se_lengthscale'.
deriv	A character, indicating according to which hyper-parameter the derivative should be computed. If NULL (default), the function simply returns the evaluation of the kernel.
vectorized	A logical value, indicating whether the function provides a vectorized version for speeded-up calculations. If TRUE, the x and y arguments should be the vector or matrix containing all inputs for which the kernel is evaluated on all pairs of elements. If FALSE, the x and y arguments are simply two inputs.

Value

A scalar, corresponding to the evaluation of the kernel.

Examples

TRUE

MagmaClustR documentation built on June 29, 2024, 1:06 a.m.