A spatial covariate-augmented overdispersed Poisson factor model is proposed to perform efficient latent representation learning method for high-dimensional large-scale spatial count data with additional covariates.
| Version: | 1.2 |
| Depends: | irlba, R (≥ 3.5.0) |
| Imports: | LaplacesDemon, stats, methods, Matrix, MASS, Rcpp (≥ 1.0.10) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2024-05-27 |
| DOI: | 10.32614/CRAN.package.SpaCOAP |
| Author: | Wei Liu [aut, cre], Qingzhi Zhong [aut] |
| Maintainer: | Wei Liu <liuwei8 at scu.edu.cn> |
| BugReports: | https://github.com/feiyoung/SpaCOAP/issues |
| License: | GPL-3 |
| URL: | https://github.com/feiyoung/SpaCOAP |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | SpaCOAP results |
| Reference manual: | SpaCOAP.pdf |
| Vignettes: |
SpaCOAP: mouse spleen dataset SpaCOAP: simulation |
| Package source: | SpaCOAP_1.2.tar.gz |
| Windows binaries: | r-devel: SpaCOAP_1.2.zip, r-release: SpaCOAP_1.2.zip, r-oldrel: SpaCOAP_1.2.zip |
| macOS binaries: | r-release (arm64): SpaCOAP_1.2.tgz, r-oldrel (arm64): SpaCOAP_1.2.tgz, r-release (x86_64): SpaCOAP_1.2.tgz, r-oldrel (x86_64): SpaCOAP_1.2.tgz |
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