Gaussian Process Modeling of Multi-Response and Possibly Noisy Datasets
An auxiliary function used in calculating the negative log-likelehood ...
Two Functions for Constructing the Correlation Matrix in GPM Package
The Plotting Function of GPM Package
The Fitting Function of GPM Package
A Set of Functions for Doing Some Calculations on Matrices in GPM Pa...
The Function for calculating the Negative Log-Likelehood in GPM Pack...
The Function for calculating the gradient of Negative Log-Likelehood i...
The Prediction Function of GPM Package
Provides a general and efficient tool for fitting a response surface to a dataset via Gaussian processes. The dataset can have multiple responses and be noisy (with stationary variance). The fitted GP model can predict the gradient as well. The package is based on the work of 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.