Type: Package
Package: slideimp
Title: Numeric Matrices K-NN and PCA Imputation
Version: 0.5.4
Authors@R: 
    person("Hung", "Pham", , "amser.hoanghung@gmail.com", role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-8271-9355"))
Description: Fast k-nearest neighbors (K-NN) and principal component
    analysis (PCA) imputation algorithms for missing values in
    high-dimensional numeric matrices, i.e., epigenetic data. For
    extremely high-dimensional data with ordered features, a sliding
    window approach for K-NN or PCA imputation is provided.  Additional
    features include group-wise imputation (e.g., by chromosome),
    hyperparameter tuning with repeated cross-validation, multi-core
    parallelization, and optional subset imputation. The K-NN algorithm is
    described in: Hastie, T., Tibshirani, R., Sherlock, G., Eisen, M.,
    Brown, P. and Botstein, D.  (1999) "Imputing Missing Data for Gene
    Expression Arrays". The PCA imputation is an optimized version of the
    imputePCA() function from the 'missMDA' package described in: Josse,
    J. and Husson, F.  (2016) <doi:10.18637/jss.v070.i01> "missMDA: A
    Package for Handling Missing Values in Multivariate Data Analysis".
License: GPL (>= 2)
URL: https://github.com/hhp94/slideimp
BugReports: https://github.com/hhp94/slideimp/issues
Depends: R (>= 4.1.0)
Imports: bigmemory, checkmate, collapse, mirai, purrr, Rcpp, stats,
        tibble
Suggests: carrier, FactoMineR, knitr, missMDA, rlang, rmarkdown,
        testthat (>= 3.0.0)
LinkingTo: mlpack, Rcpp, RcppArmadillo, RcppEnsmallen
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
NeedsCompilation: yes
Packaged: 2025-12-23 03:37:27 UTC; amser
Author: Hung Pham [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-8271-9355>)
Maintainer: Hung Pham <amser.hoanghung@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-07 09:20:02 UTC
Built: R 4.5.1; x86_64-apple-darwin20; 2026-01-07 11:18:05 UTC; unix
Archs: slideimp.so.dSYM
