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biokNN
View on CRAN: Click
here
Download and install biokNN package within the R console
Install from CRAN:
install.packages("biokNN")
Install from Github:
library("remotes")
install_github("cran/biokNN") Install by package version:
library("remotes")
install_version("biokNN", "0.1.0") Attach the package and use:
library("biokNN")
Maintained by
Maximiliano Cubillos
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-04-22
Latest Update:
Description:
The bi-objective k-nearest neighbors method biokNN is an imputation method designed to estimate missing values on data with a multilevel structure. The original algorithm is an extension of the k-nearest neighbors method proposed by Bertsimas et al. 2017 httpsjmlr.orgpapersv1817-073.html using a bi-objective approach. A brief description of the method can be found in Cubillos 2021 httpspure.au.dkportalfiles214627979biokNN.pdf. The biokNN package provides an R implementation of the method for datasets with continuous variables e.g. employee productivity student grades and a categorical class variable e.g. department school. Given an incomplete dataset with such structure this package produces complete datasets using both single and multiple imputation including visualization tools to better understand the pattern of the missing values.
How to cite:
Maximiliano Cubillos (2021). biokNN: Bi-Objective k-Nearest Neighbors Imputation for Multilevel Data. R package version 0.1.0, https://cran.r-project.org/web/packages/biokNN. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.1.0 (2021-04-22 09:20)
Other packages that cited biokNN R package
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Other R packages that biokNN depends,
imports, suggests or enhances
Functions, R codes and Examples using
the biokNN R package
Some associated functions: biokNN.impute.mi . biokNN.impute . calibrate . create.multilevel . data.example . missing.plot . pattern.plot . target.boxplot .
Some associated R codes: Globals.R . data.R . dataGeneration.R . extra.R . impute.R . Full biokNN package functions and examples
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