CorrMat {GPM}

Two Functions for Constructing the Correlation Matrix in GPM Package

Description

The CorrMat_Sym() function builds the auto-correlation matrix corresponding to dataset X while the CorrMat_Vec() function builds the correlation matrix between datasets X1 and X2.

Usage

CorrMat_Sym(X, CorrType, Omega)
CorrMat_Vec(X1, X2, CorrType, Omega)

Arguments

X, X1, X2

Matrices containing the numeric data points. The rows and columns of both X1 and X2 denote individual observation settings and dimension, respectively.

CorrType

The correlation function of the GP model. Choices include 'G' (default), 'PE', 'LBG', and 'LB'. See the references for the details.

Omega

The vector storing all the scale (aka roughness) parameters of the correlation function. The length of Omega depends on the CorrType. See reference 1.

Value

R The Correlation matrix with size nrow(X1)-by-nrow(X2). See here.

Note

This function is NOT exported once the GPM package is loaded.

References

1. Bostanabad, R., Kearney, T., Tao, S. Y., Apley, D. W. & Chen, W. (2018) Leveraging the nugget parameter for efficient Gaussian process modeling. International Journal for Numerical Methods in Engineering, 114, 501-516.

2. Plumlee, M. & Apley, D. W. (2017) Lifted Brownian kriging models. Technometrics, 59, 165-177.

See Also

Fit to see how a GP model can be fitted to a training dataset.
Predict to use the fitted GP model for prediction.
Draw to plot the response via the fitted model.

Examples

# see the examples in \code{\link[GPM]{Fit}}