Everybody is talking about robustness but nobody is checking/measuring/writing/publishing about it. What it is this animal called "robustness"?
The package contains an attempted to measure it in the same way the accuracy is assessed. We understand that a model is robust if the estimates and generated results are fairly stable following gradual changes in input data or model specification.
What if the results are changing to little following a reasonable change in the input data? Is this model more robust than a model that changes in a "proportional" manner? What if the changes are to large? When is "to large" to large?
We are interested to learn about the best practices and implement them here. Help.
Everybody is talking about robustness but nobody is checking/measuring/writing/publishing about it. What it is this animal called "robustness"?
The package contains an attempted to measure it in the same way the accuracy is assessed. We understand that a model is robust if the estimates and generated results are fairly stable following gradual changes in input data or model specification.
What if the results are changing to little following a reasonable change in the input data? Is this model more robust than a model that changes in a "proportional" manner? What if the changes are to large? When is "to large" to large?
We are interested to learn about the best practices and implement them here. Help.