CKNNRLD: Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data

Implements the 'CKNNRLD' algorithm (Clustering-Based K-Nearest Neighbor Regression for Longitudinal Data) for improving K-Nearest Neighbor ('KNN') regression on longitudinal data through cluster-based partitioning and localized prediction. Offers enhanced computational efficiency and accuracy for high-volume longitudinal datasets. The clustering is performed using the 'latrend' package, which provides a unified interface for various longitudinal clustering methods including 'KML' (K-Means for Longitudinal data). The acronym 'KNN' stands for K-Nearest Neighbor. The acronym 'KML' stands for K-Means for Longitudinal data. References: Loeloe MS, Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025). "Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach." BMC Bioinformatics, 26, 232. <doi:10.1186/s12859-025-06205-1>; Genolini C, Falissard B (2010). "KmL: k-means for longitudinal data." Computational Statistics, 25(2), 317-328. <doi:10.1007/s00180-009-0178-4>.

Getting started

Package details

AuthorMohammad Sadegh Loeloe [aut, cre], Seyyed Mohammad Tabatabaei [aut], Reyhane Sefidkar [aut], Amir Houshang Mehrparvar [aut], Sara Jambarsang [aut, ths]
MaintainerMohammad Sadegh Loeloe <mslbiostat@gmail.com>
LicenseGPL-3
Version0.1.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("CKNNRLD")

Try the CKNNRLD package in your browser

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

CKNNRLD documentation built on May 29, 2026, 1:06 a.m.