wNNSel: Weighted Nearest Neighbor Imputation of Missing Values using Selected Variables

New tools for the imputation of missing values in high-dimensional data are introduced using the non-parametric 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 high-dimensional data when the sample size is smaller than the number of predictors. For more information see Faisal and Tutz (2017) <doi:10.1515/sagmb-2015-0098>.

Package details

AuthorShahla Faisal
MaintainerShahla Faisal <s[email protected]>
LicenseGPL-2
Version0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("wNNSel")

Try the wNNSel package in your browser

Any scripts or data that you put into this service are public.

wNNSel documentation built on Nov. 17, 2017, 7:59 a.m.