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Specifically, the rates lambda and omega are expected a priori to vary with time of day, so defining "surveys" (# = nsurveys) as 15-minute files could make the posteriors of these rates multimodal.
It's not clear how / whether this would affect the estimates.
We could add an aggregation period argument (file / day) to the ML data tabulation API and do a controlled experiment with both of its settings.
The text was updated successfully, but these errors were encountered:
Specifically, the rates lambda and omega are expected a priori to vary with time of day, so defining "surveys" (# = nsurveys) as 15-minute files could make the posteriors of these rates multimodal.
It's not clear how / whether this would affect the estimates.
We could add an aggregation period argument (file / day) to the ML data tabulation API and do a controlled experiment with both of its settings.
The text was updated successfully, but these errors were encountered: