Carries out a gaussian process regression with a linear kernel (dot product). For internal use only!
gaussian_process(X, Y, noisev, scale)a list containing the following elements:
b the regression coefficients.
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.
a matrix of predictor variables
a matrix with a single response variable
a value indicating the variance of the noise for Gaussian process regression. Default is 0.001. a matrix with a single response variable
a logical indicating whether both the predictors and the response variable must be scaled to zero mean and unit variance.
Leonardo Ramirez-Lopez