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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "wNNSel" in publications use:'
type: software
license: GPL-2.0-only
title: 'wNNSel: Weighted Nearest Neighbor Imputation of Missing Values using Selected
  Variables'
version: '0.1'
doi: 10.32614/CRAN.package.wNNSel
abstract: 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) <https://doi.org/10.1515/sagmb-2015-0098>.
authors:
- family-names: Faisal
  given-names: Shahla
  email: shahla_ramzan@yahoo.com
repository: https://shahlafaisal.r-universe.dev
commit: f846e1075256b85fa9c455bb34e6fabd1b7a26f2
date-released: '2017-11-09'
contact:
- family-names: Faisal
  given-names: Shahla
  email: shahla_ramzan@yahoo.com