Package: BigDataStatMeth
Type: Package
Title: Scalable Statistical Computing with HDF5-Backed Matrices
Version: 2.0.4
Date: 2026-07-17
Authors@R: 
    c(
        person( given = "Dolors", 
                family = "Pelegri-Siso", 
                email = "dolors.pelegri@isglobal.org", 
                role=c("aut", "cre"),
                comment = c(ORCID = "0000-0002-5993-3003")),
        person( given = "Juan R.", 
                family = "Gonzalez", 
                email = "juanr.gonzalez@isglobal.org", 
                role = c("aut"), 
                comment = c(ORCID = "0000-0003-3267-2146"))
        )
Description: A framework for 'scalable' statistical computing on large on-disk 
    matrices stored in 'HDF5' files. It provides efficient block-wise 
    implementations of core linear-algebra operations (matrix multiplication, 
    SVD, PCA, and QR decomposition) written in C++ and R, along with building 
    blocks from which higher-level multivariate methods such as canonical 
    correlation analysis can be constructed. These building blocks are designed 
    not only for direct use, but also as foundational components for developing 
    new statistical methods that must operate on datasets too large to fit in 
    memory. The package supports data provided either as 'HDF5' files or 
    standard R objects, and is intended for high-dimensional applications such 
    as 'omics' and precision-medicine research.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: data.table, Rcpp (>= 1.0.6), RCurl, utils, R6
LinkingTo: Rcpp, RcppEigen, Rhdf5lib
Suggests: Matrix, BiocStyle, knitr, rmarkdown, ggplot2, MASS
SystemRequirements: GNU make, C++17
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 7.3.3
NeedsCompilation: yes
Author: Dolors Pelegri-Siso [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-5993-3003>),
  Juan R. Gonzalez [aut] (ORCID: <https://orcid.org/0000-0003-3267-2146>)
Maintainer: Dolors Pelegri-Siso <dolors.pelegri@isglobal.org>
Packaged: 2026-07-18 14:50:11 UTC; mailos
Repository: CRAN
Date/Publication: 2026-07-19 07:20:20 UTC
Built: R 4.5.3; x86_64-w64-mingw32; 2026-08-28 23:49:58 UTC; windows
Archs: x64
