# How to do multiple imputation on Julia?

**URL:** <https://discourse.julialang.org/t/how-to-do-multiple-imputation-on-julia/17713>\
**Category:** Statistics\
**Created:** [November 19, 2018, 12:54pm UTC](https://discourse.julialang.org/t/how-to-do-multiple-imputation-on-julia/17713 "2018-11-19T12:54:23Z")\
**Posts on this page:** 1\
**Showing post:** 15

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**Author:** ![Albert\_Zevelev](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/albert_zevelev/32/11844_2.png) [@Albert\_Zevelev](https://discourse.julialang.org/u/Albert_Zevelev)\
**Post date:** [April 25, 2020, 10:57pm UTC](https://discourse.julialang.org/t/how-to-do-multiple-imputation-on-julia/17713/15 "2020-04-25T22:57:53Z")

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Another vote from me for more advanced data imputation in Julia!  
The R pkg Multiple Imputation by Chained Equations ([MICE](https://github.com/stefvanbuuren/mice)) is super-popular but also super-slow.  
This is where Julia can shine!  
Data imputation is often one of the first steps in any ML project (or Kaggle competition).  
This kind of feature can help make the case: [Getting Julia support to Kaggle](https://discourse.julialang.org/t/getting-julia-support-to-kaggle/2121/19)

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