pPCA
1.1Partial 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
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 50%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- 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
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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