gaussian_process | R Documentation |
Carries out a gaussian process regression with a linear kernel (dot product). For internal use only!
gaussian_process(X, Y, noisev, scale)
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. |
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
.
Leonardo Ramirez-Lopez
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