Package: SpaCOAP 1.2

SpaCOAP: High-Dimensional Spatial Covariate-Augmented Overdispersed Poisson Factor Model

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.

Authors:Wei Liu [aut, cre], Qingzhi Zhong [aut]

SpaCOAP_1.2.tar.gz
SpaCOAP_1.2.zip(r-4.7)SpaCOAP_1.2.zip(r-4.6)SpaCOAP_1.2.zip(r-4.5)
SpaCOAP_1.2.tgz(r-4.6-x86_64)SpaCOAP_1.2.tgz(r-4.6-arm64)SpaCOAP_1.2.tgz(r-4.5-x86_64)SpaCOAP_1.2.tgz(r-4.5-arm64)
SpaCOAP_1.2.tar.gz(r-4.7-arm64)SpaCOAP_1.2.tar.gz(r-4.7-x86_64)SpaCOAP_1.2.tar.gz(r-4.6-arm64)SpaCOAP_1.2.tar.gz(r-4.6-x86_64)
SpaCOAP_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
SpaCOAP/json (API)

# Install 'SpaCOAP' in R:
install.packages('SpaCOAP', repos = c('https://feiyoung.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/feiyoung/spacoap/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

4.00 score 191 downloads 3 exports 7 dependencies

Last updated from:5411bd6c8e. Checks:11 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING144
linux-devel-x86_64WARNING153
source / vignettesOK232
linux-release-arm64WARNING142
linux-release-x86_64WARNING145
macos-release-arm64WARNING111
macos-release-x86_64WARNING298
macos-oldrel-arm64WARNING106
macos-oldrel-x86_64WARNING437
windows-develWARNING152
windows-releaseWARNING127
windows-oldrelWARNING152
wasm-releaseOK114

Exports:chooseParamsgendata_spacoapSpaCOAP

Dependencies:irlbaLaplacesDemonlatticeMASSMatrixRcppRcppArmadillo

SpaCOAP: mouse spleen dataset
Data preparation | Obtain data matrices and tunning parameters | Determine the structure dimension | Fitting SpaCOAP | Compare SpaCOAP and other methods | Summarize the metrics

Last update: 2024-05-28
Started: 2024-05-26

SpaCOAP: simulation
Generate the simulated data | Compare with other methods | Visualize the comparison of performance | Select the parameters

Last update: 2024-05-26
Started: 2024-05-26