Description
A module where you can use a statistical method (thousand error, hb, etc.) to detect outliers, select an imputation method, get a preview of how the imputation would look, and then choose to commit changes or rollback to change paramteres.
Optionally make cell level changes to the data before committing.
This feature involves refactoring existing method module(s) from being separate visualizations to being a single method module which also offers imputation features. It also needs to log which parameteres were used during imputation in a transparent and reproducible way, preferably through logging "what happened, how and when".
Description
A module where you can use a statistical method (thousand error, hb, etc.) to detect outliers, select an imputation method, get a preview of how the imputation would look, and then choose to commit changes or rollback to change paramteres.
Optionally make cell level changes to the data before committing.
This feature involves refactoring existing method module(s) from being separate visualizations to being a single method module which also offers imputation features. It also needs to log which parameteres were used during imputation in a transparent and reproducible way, preferably through logging "what happened, how and when".