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Currently, the dataset to which a certain model is applied for optimisation is specified in the model.yaml file. Multiple datasets can also be specified in the same model.yaml, giving an overall fit result.
Is there a built-in option to perform a series of optimisations on multiple datasets, using the same model, but otherwise in isolation from each other, such that the result of any optimisation is not influenced by the others?
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Currently, the dataset to which a certain model is applied for optimisation is specified in the model.yaml file. Multiple datasets can also be specified in the same model.yaml, giving an overall fit result.
Is there a built-in option to perform a series of optimisations on multiple datasets, using the same model, but otherwise in isolation from each other, such that the result of any optimisation is not influenced by the others?
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