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) <doi:10.1515/sagmb20150098>.
Package details 


Author  Shahla Faisal 
Maintainer  Shahla Faisal <s[email protected]> 
License  GPL2 
Version  0.1 
Package repository  View on CRAN 
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