individual_errors {hmer}

Predictive Error Plots

Description

Plots the predictive error with respect to a variety of quantities.

Usage

individual_errors(
  em,
  validation,
  errtype = "normal",
  xtype = "index",
  plottype = "normal"
)

Arguments

em

The emulator to perform diagnostics on

validation

The validation set of points with output(s)

errtype

The type of individual error to be plotted.

xtype

The value to plot against

plottype

Whether to plot a standard or Q-Q plot.

Details

The choice of errors to plot is controlled by errtype, and can be one of four things: normal, corresponding to the regular standardised errors; eigen, corresponding to the errors after reordering given by the eigendecomposition of the emulator covariance matrix; chol, similarly deriving errors after Cholesky decomposition; and cholpivot, deriving the errors after pivoted Cholesky decomposition.

What the errors are plotted with respect to is controlled by xtype. The options are index, which plots them in their order in the validation set; em, which plots errors with respect to the emulator prediction at that point; and any named parameter of the model, which plots with respect to the values of that parameter.

Finally, the plot type is controlled by plottype: this can be one of normal, which plots the errors; or qq, which produces a Q-Q plot of the errors.

The default output is to plot the standardised errors (with no decomposition) against the ordering in the validation set; i.e. errtype = "normal", xtype = "index", plottype = "normal".

Some combinations are not permitted, as the output would not be meaningful. Errors arising from an eigendecomposition cannot be plotted against either emulator prediction or a particular parameter (due to the transformation induced by the eigendecomposition); Q-Q plots are not plotted for a non-decomposed set of errors, as the correlation between errors makes it much harder to interpret.

Value

The relevant plot.

References

Bastos & O'Hagan (2009) <doi:10.1198/TECH.2009.08019>

See Also

Other diagnostic functions: analyze_diagnostic(), classification_diag(), comparison_diag(), get_diagnostic(), residual_diag(), standard_errors(), summary_diag(), validation_diagnostics()

Examples

i1 <- individual_errors(SIREmulators$ems$nS, SIRSample$validation)
i2 <- individual_errors(SIREmulators$ems$nS, SIRSample$validation, "chol", "em")
i3 <- individual_errors(SIREmulators$ems$nS, SIRSample$validation, "eigen", plottype = "qq")
i4 <- individual_errors(SIREmulators$ems$nS, SIRSample$validation, "cholpivot", xtype = "aSI")