A Method for Handling Missing Values in Prediction Applications R package toweranNA version 0.1.0 CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData) Non-imputational method for handling missing values in a prediction context, meaning that not only are there missing values in the training dataset, but also some values may be missing in future cases to be predicted. Based on the notion of regression averaging (Matloff (2017, ISBN: 9781498710916)). Software Depends: R (>= 3.6.0),regtools (>= 0.8.0),rmarkdown Imports: FNN, pdist, stats Norm Matloff <nsmatloff@ucdavis.edu> Comprehensive R Archive Network (CRAN) Norm Matloff [aut, cre] (ORCID: <https://orcid.org/0000-0001-9179-6785>), Pete Mohanty [aut] (ORCID: <https://orcid.org/0000-0001-8531-3345>) GPL (>= 2) 2023-03-15 application/tgz https://CRAN.R-project.org/package=toweranNA doi:10.32614/CRAN.package.toweranNA