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philchalmers committed Nov 1, 2024
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On occasion functions will return `warning` message that either boarder on (or should be treated as) error messages if they influence the veracity of the simulation results. Such examples may include models that appear to 'converge' but do so with non-nonsensical parameter estimates (e.g., negative variances, non-positive definite correlation matrices, maximum iterations reached in an numerical searching algorithm, etc). However, because such issues are non-fatal third-party software (i.e., functions not written by the developer of the simulation) may simply raise a `warning` message for further inspection, whereas in a Monte Carlo simulation experiment such issues should generally be treated as invalid (though their frequency of occurrence should still be tracked, as is the default in `SimDesign`).
On occasion functions will return `warning` message that either border on (or should be treated as) error messages if they influence the veracity of the simulation results. Such examples may include models that appear to 'converge' but do so with non-nonsensical parameter estimates (e.g., negative variances, non-positive definite correlation matrices, maximum iterations reached in an numerical searching algorithm, etc). However, because such issues are non-fatal third-party software (i.e., functions not written by the developer of the simulation) may simply raise a `warning` message for further inspection, whereas in a Monte Carlo simulation experiment such issues should generally be treated as invalid (though their frequency of occurrence should still be tracked, as is the default in `SimDesign`).

To resolve this issue, and to avoid using a more nuclear option such as setting `option(warn=2)` to treat *all* warnings as errors in the simulation, the function `manageWarnings()` can be used to explicit convert known warning message strings into errors that disrupt the code execution while allowing other warning messages to continue to be raised.

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