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This paper proposes a way of formally assessing prior-data conflict and sensitivity. Might be a very nice plus once all of the building blocks are in place.
The text was updated successfully, but these errors were encountered:
I am not sure of how efficient his method is if it still needs to use sampling methods to obtain the posterior.
For variance-based sensitivity, which is defined here, and simple inference models with closed form solutions, we can indeed save computations by computing the variance from the parameters of the posterior, and using that to calculate first order or higher order sensitivities.
This paper proposes a way of formally assessing prior-data conflict and sensitivity. Might be a very nice plus once all of the building blocks are in place.
The text was updated successfully, but these errors were encountered: