Comparing GLM-PCA to Traditional PCA | Poisson likelihood | Negative binomial likelihood | Standard PCA | Visualize results | Examining the GLM-PCA output
Package: glmpca 0.2.0.9000
glmpca: Dimension Reduction of Non-Normally Distributed Data
Implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices. Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) <doi:10.1186/s13059-019-1861-6>. Townes FW (2019) <arxiv:1907.02647>.
Authors:
glmpca_0.2.0.9000.tar.gz
glmpca_0.2.0.9000.zip(r-4.7)glmpca_0.2.0.9000.zip(r-4.6)glmpca_0.2.0.9000.zip(r-4.5)
glmpca_0.2.0.9000.tgz(r-4.6-any)glmpca_0.2.0.9000.tgz(r-4.5-any)
glmpca_0.2.0.9000.tar.gz(r-4.7-any)glmpca_0.2.0.9000.tar.gz(r-4.6-any)
glmpca_0.2.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
glmpca/json (API)
| # Install 'glmpca' in R: |
| install.packages('glmpca', repos = c('https://willtownes.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/willtownes/glmpca/issues
Last updated from:0536890a3a. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 124 | ||
| source / vignettes | OK | 206 | ||
| linux-release-x86_64 | OK | 115 | ||
| macos-release-arm64 | OK | 137 | ||
| macos-oldrel-arm64 | OK | 174 | ||
| windows-devel | OK | 66 | ||
| windows-release | OK | 84 | ||
| windows-oldrel | OK | 79 | ||
| wasm-release | OK | 98 |
Exports:glmpca
Dependencies:MASS
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| GLM-PCA | glmpca |
| Predict Method for GLM-PCA Fits | predict.glmpca |
