compute_gram_matrix: Gram Matrix Computation

In GreedyExperimentalDesign: Greedy Experimental Design Construction

Gram Matrix Computation

Description

Computes the Gram Matrix for a user-specified kernel using the library kernlab. Note that this function automatically standardizes the columns of the data entered.

Usage

compute_gram_matrix(X, kernel_type, params = c())

Arguments

X	The design matrix with $n$ rows (one for each subject) and $p$ columns (one for each measurement on the subject). This is the design matrix you wish to search for a more optimal design.
kernel_type	One of the following: "vanilla", "rbf", "poly", "tanh", "bessel", "laplace", "anova" or "spline".
params	A vector of numeric parameters. Each kernel_type has different numbers of parameters required. For more information see documentation for the kernlab library.

Value

The n x n gram matrix for the given kernel on the given data.

Author(s)

Adam Kapelner

GreedyExperimentalDesign documentation built on July 26, 2023, 5:48 p.m.