resemble (version 1.2.2)

gprdp: Gaussian process regression with linear kernel (gprdp)

Description

Carries out a gaussian process regression with a linear kernel (dot product). For internal use only!

Usage

gprdp(X, Y, noisev, scale)

Arguments

X

a matrix of predictor variables

Y

a matrix with a single response variable

noisev

a value indicating the variance of the noise for Gaussian process regression. Default is 0.001. a matrix with a single response variable

scale

a logical indicating whether both the predictors and the response variable must be scaled to zero mean and unit variance.

Value

a list containing the following elements:

• Xz the (final transformed) matrix of predictor variables.
• alpha the alpha matrix.
• is.scaled logical indicating whether both the predictors and response variable were scaled to zero mean and unit variance.
• Xcenter if matrix of predictors was scaled, the centering vector used for X.
• Xscale if matrix of predictors was scaled, the scaling vector used for X.
• Ycenter if matrix of predictors was scaled, the centering vector used for Y.
• Yscale if matrix of predictors was scaled, the scaling vector used for Y.