New tools for the imputation of missing values in highdimensional
data are introduced using the nonparametric nearest neighbor methods. It
includes weighted nearest neighbor imputation methods that use specific
distances for selected variables. It includes an automatic procedure of cross
validation and does not require prespecified values of the tuning parameters.
It can be used to impute missing values in highdimensional data when the sample
size is smaller than the number of predictors. For more information see Faisal
and Tutz (2017)
Package details 


Author  Shahla Faisal 
Date of publication  20171109 11:32:18 UTC 
Maintainer  Shahla Faisal <[email protected]> 
License  GPL2 
Version  0.1 
Package repository  View on CRAN 
Installation 
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