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A computationally-efficient leading-eigenvalue approximation to tail probabilities and quantiles of large quadratic forms, in particular for the Sequence Kernel Association Test (SKAT) used in genomics <doi:10.1002/gepi.22136>. Also provides stochastic singular value decomposition for dense or sparse matrices.
| Version: | 1.6 |
| Depends: | R (≥ 2.10), methods |
| Imports: | svd, CompQuadForm, Matrix, stats, coxme |
| Suggests: | knitr, rmarkdown, SKAT |
| Published: | 2021-11-23 |
| Author: | Thomas Lumley |
| Maintainer: | Thomas Lumley <t.lumley at auckland.ac.nz> |
| License: | GPL-2 |
| URL: | https://github.com/tslumley/bigQF |
| NeedsCompilation: | yes |
| CRAN checks: | bigQF results |
| Reference manual: | bigQF.pdf |
| Vignettes: |
Checking pQF vs SKAT Matrix-free computations SKAT, weights, and projections |
| Package source: | bigQF_1.6.tar.gz |
| Windows binaries: | r-devel: bigQF_1.6.zip, r-release: bigQF_1.6.zip, r-oldrel: bigQF_1.6.zip |
| macOS binaries: | r-release (arm64): bigQF_1.6.tgz, r-oldrel (arm64): bigQF_1.6.tgz, r-release (x86_64): bigQF_1.6.tgz, r-oldrel (x86_64): bigQF_1.6.tgz |
| Old sources: | bigQF archive |
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