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BigDataStatMeth
View on CRAN: Click
here
Download and install BigDataStatMeth package within the R console
Install from CRAN:
install.packages("BigDataStatMeth")
Install from Github:
library("remotes")
install_github("cran/BigDataStatMeth") Install by package version:
library("remotes")
install_version("BigDataStatMeth", "2.0.6") Attach the package and use:
library("BigDataStatMeth")
Maintained by
Dolors Pelegri-Siso
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-29
Latest Update: 2025-11-29
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, QR decomposition, and canonical correlation analysis) written in C++ and R. 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.
How to cite:
Dolors Pelegri-Siso (2025). BigDataStatMeth: Scalable Statistical Computing with HDF5-Backed Matrices. R package version 2.0.6, https://cran.r-project.org/web/packages/BigDataStatMeth. Accessed 24 Oct. 2026.
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