v1.5.0

hmer 1.5.0

Major changes

• Change to nomenclature: all xx_emulator_from_data functions are now a single function; variance_emulator_from_data and bimodal_emulator_from_data are now called using emulator_from_data with argument emulator_type = 'variance' and emulator_type = 'multistate' respectively. To avoid confusion about the output of the function, generate_new_runs has been renamed to generate_new_design. Older functions have been deprecated and will be removed in a subsequent version.

Bug fixes

• Changes to generate_new_design to avoid implausibility asymptoting in edge cases.

• Explicit checks included to ensure that ordering of parameter ranges matches with data.frames provided for training

• Fixes to ensure that 1d systems behave as expected.

• Fix to avoid singular correlation matrices in some situations where corr_type = 'exp_sq'.

• Fixes for edge-case multistate emulator training problems, and for situations where model.matrix behaviour fails (due to deparse truncation issues in core R functions).

Enhancements

• Modifications to emulator design via emulator_from_data: in particular hyperparameter estimation has been made more robust; emulator regression surfaces now support cubic terms; variance and multistate emulators now more robust to different numbers of repetitions at different input sites.

• Covariance emulation introduced (via emulator_from_data(..., emulator_type = 'covariance')), allowing a full covariance matrix to be robustly emulated. Results are presented using a prototype emulator matrix EmulatedMatrix to efficiently make predictions, including checks to ensure that predicted matrices are semi-positive definite. In the future, covariance matrices will be supported in implausibility measures and point proposals.