Partial Principal Component Analysis of Partitioned Large Sparse Matrices
Overview
Performs partial principal component analysis of a large sparse matrix. The matrix may be stored as a list of matrices to be concatenated (implicitly) horizontally. Useful application includes cases where the number of total nonzero entries exceed the capacity of 32 bit integers (e.g., with large Single Nucleotide Polymorphism data).
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 50%
Downloads
Dependencies
Installing pPCA adds 3 packages (3 with compiled code, 3.6 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppEigen 1.7 MB, RSpectra 125 KB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.1Latest
- 1.02024-10-11
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-10-11
- Total releases
- 2 / 2 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.0.2
- Download size
- 7.1 KB
Cite
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