validateEmulatorApp: validating the emulator emulator

In OakleyJ/MUCM: Gaussian process emulator methods based on the MUCM toolkit

Description

validating the emulator emulator

Usage

validateEmulatorApp(emulator, new.inputs = NULL, new.outputs = NULL,
  emulator.predictions = NULL, verbose = FALSE, ...)

Arguments

emulator	A fit object of class inheriting from 'emulatorFit'.
new.inputs	A data matrix of input(s) at which emulation is desired (new inputs). Must contain at least all parameters given in emulator$training.inputs. (Ensure they are the same used to generate the emulator.predictions.)
new.outputs	A matrix outputs used to validate the emulator predictions. This Matrix must have columns equal to the number of outputs.
emulator.predictions	Output generated from the predict.emulatorFit function. It is an optional argument. If this is not provided it will be calculated using arguments provided. Note Posterior Variance will be calculated, unless you provide this argument.
verbose	Defaults to TRUE. If FALSE, text under graphs (explanations) will not appear.

Examples

# Fit the emulator
fit <- fitEmulator(inputs = surfebm[1:25, 1:2], 
                   outputs = surfebm[1:25, 3, drop = FALSE])

# Use fitted emulator to predict posterior means and variances at the new points
predictions <- predict(fit, surfebm[26:35, 1:2], sd = FALSE, var.cov = TRUE)

# Compare predictions with true values for the new inputs
# Can also compare accuracy of prediction based on posterior variance
validateEmulatorApp(fit, surfebm[26:35, 1:2], surfebm[26:35, 3], predictions, verbose = FALSE, launch.browser = TRUE)

OakleyJ/MUCM documentation built on May 7, 2019, 9:01 p.m.