Description Usage Arguments Value Author(s) References Examples
Evaluates frequentist performance of the GASP.
1 | NGASPmetrics(GASP, true_output, ref_output)
|
GASP |
GASP emulator. |
true_output |
Output from the simulator. |
ref_output |
Heuristic emulator output. |
List of performance measures.
RMSPE_base |
Root mean square predictive error with respect to the heuristic emulator output. |
RMSPE |
Root mean square predictive error for the emulator output |
ratio |
ratio of RMSPE_base to RMSPE. Ratio = RMSPE_base/RMSPE |
CIs |
95% central credible intervals |
emp_cov |
95% empirical coverage within the CIs |
length_CIs |
Average lenght of 95% central credible intervals |
Ksenia N. Kyzyurova, ksenia.ucoz.net
Ksenia N. Kyzyurova, James O. Berger, and Robert L. Wolpert. Coupling computer models through linking their statistical emulators. SIAM/ASA Journal on Uncertainty Quantification, 6(3): 1151-1171, 2018
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ## Function f1 is a simulator
f1<-function(x){sin(pi*x)}
## One-dimensional inputs are x1
x1 <- seq(-1,1,.37)
## The following contains the list of data inputs (training) and outputs (fD) together with
## the assumed fixed smoothness of a computer model output.
data.f1 <- list(training = x1,fD = f1(x1), smooth = 1.99)
## Evaluation of GASP parameters
f1_MLEs = eval_GASP_RFP(data.f1,list(function(x){x^0},function(x){x^1}),1,FALSE)
## Evaluate the emulator
xn = seq(-1,1,.01)
GASP_type2_f1 <- eval_type2_GASP(as.matrix(xn),f1_MLEs)
## Plot the emulator
par(mar = c(6.1, 6.1, 5.1, 2.1))
GASP_plot(GASP_type2_f1,data = data.f1,emul_type = "",ylim = ylim, plot_training = TRUE)
## Measure performance of an emulator
NGASPmetrics(GASP_type2_f1,f1(xn),mean(f1(xn)))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.