GPM (version 3.0.0)

Draw: The Plotting Function of GPM Package

Description

Plots the predicted response along with the assocaited uncertainty via the GP model fitted by Fit. Accepts multi-input and multi-output models. See Arguments for more details on the options.

Usage

Draw(Model, Plot_wrt, LB = NULL, UB = NULL, Values = NULL,
  Response_ID = NULL, res = 15, X1Label = NULL, X2Label = NULL,
  YLabel = NULL, Title = NULL, PI95 = NULL)

Arguments

Model

The GP model fitted by Fit.

Plot_wrt

A binary vector of length p where p is the dimension of the inputs in Model. A maximum (minimum) of 2 (1) elements can be 1. The elemenets set to 1, would correspond to the plotting axes.

LB, UB

Vectors of length sum(Plot_wrt) indicating the lower and upper bounds used for plotting. The first (second) element corresponds to the first (second) non-zero element of Plot_wrt.

Values

A vector of length p-sum(Plot_wrt). The values are assigned to the variables NOT used in plotting and correspond to the zeros in Plot_wrt.

Response_ID

A positive integer indicating the response that should be plotted if Model is multi-response.

res

A positive integer indicating the number of points used in plotting. Higher values will result in smoother plots.

X1Label

A string for the label of axis 1.

X2Label

A string for the label of axis 2, if plotting a surface.

YLabel

A string for the label of the response axis.

Title

A string for the title of the plot.

PI95

Flag (a scalar) indicating whether the 95% prediction interval should be plotted. Set it to a non-zero value to turn the flag "on".

References

  1. Bostanabad, R., Kearney, T., Tao, S., Apley, D. W. & Chen, W. (2018) Leveraging the nugget parameter for efficient Gaussian process modeling. Int J Numer Meth Eng, 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.

Examples

Run this code
# NOT RUN {
# See the examples in the fitting function.
# }

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