pPCA: Partial Principal Component Analysis of Partitioned Large Sparse
Matrices
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).
| Version: |
1.1 |
| Depends: |
R (≥ 3.0.2), methods, RSpectra (≥ 0.16-1) |
| Imports: |
Matrix (≥ 1.1-0), Rcpp (≥ 0.11.5) |
| LinkingTo: |
Rcpp |
| Suggests: |
ggbiplot |
| Published: |
2024-10-22 |
| Author: |
Srika Raja [aut, cre],
Somak Dutta [aut] |
| Maintainer: |
Srika Raja <sri1919 at iastate.edu> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| CRAN checks: |
pPCA results |
Documentation:
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