How to do multiple imputation on Julia?


#1

I’ve found the package Impute.jl but it seems it’s only able to use these simple methods:

  • drop - remove missing
  • locf - last observation carried forward
  • nocb - next observation carried backward
  • interp - linear interpolation of values in vector
  • fill - replace with a specific value or a function which returns a value given the existing vector with missing values dropped.

How can I do multiple imputation when I have several variables or I want to use more complex methods, for example using: fully conditional specification (chained equations, mice), bayesian methods, random forest, multilevel imputation, nested imputation, censored data, categorical data, survival data…


What features will I miss in Julia?
What features will I miss in Julia?
#2

The same way as you would estimate any parameter.


#3

I mean without coding all the process on my own but with a package that does the imputation automatically. Other tools do have it (R, Stata, SAS…).