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There are 3 types of missing data : MCAR, MAR and MNAR. In the imputer selection process, we must choose a holes generator. It would be suitable to select a holes generator that reflects the holes present in the dataset. The aim is to provide a tool for characterizing the user's hole type.
Current situation :
No tool available today in Qolmat.
Improvement sought :
Provide a tool to characterize the user's hole present in his/her dataset. We should first to test if data are MCAR or not.
================== Tasks ==================
Implement the Little's Test in case of two variables iid where only one is missing.
Implement the Little's test with multiple variable variables and missing patterns and known parameters.
Implement the Little's test with multiple variable variables and missing patterns and unknown parameters.
The text was updated successfully, but these errors were encountered:
Why ?
There are 3 types of missing data : MCAR, MAR and MNAR. In the imputer selection process, we must choose a holes generator. It would be suitable to select a holes generator that reflects the holes present in the dataset. The aim is to provide a tool for characterizing the user's hole type.
Current situation :
No tool available today in Qolmat.
Improvement sought :
Provide a tool to characterize the user's hole present in his/her dataset. We should first to test if data are MCAR or not.
================== Tasks ==================
The text was updated successfully, but these errors were encountered: