Package: gjam 2.6.2

James S. Clark

gjam: Generalized Joint Attribute Modeling

Analyzes joint attribute data (e.g., species abundance) that are combinations of continuous and discrete data with Gibbs sampling. Full model and computation details are described in Clark et al. (2018) <doi:10.1002/ecm.1241>.

Authors:James S. Clark, Daniel Taylor-Rodriquez

gjam_2.6.2.tar.gz
gjam_2.6.2.tar.gz(r-4.5-noble)gjam_2.6.2.tar.gz(r-4.4-noble)
gjam_2.6.2.tgz(r-4.4-emscripten)gjam_2.6.2.tgz(r-4.3-emscripten)
gjam.pdf |gjam.html✨
gjam/json (API)

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

Peer review:

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

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.16 score 144 scripts 658 downloads 1 mentions 17 exports 4 dependencies

Last updated 3 years agofrom:296c89707a. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-linux-x86_64NOTENov 16 2024

Exports:gjamgjamCensorYgjamConditionalParametersgjamDeZerogjamFillMissingTimesgjamIIEgjamIIEplotgjamOrdinationgjamPlotgjamPoints2GridgjamPredictgjamPriorTemplategjamReZerogjamSensitivitygjamSimDatagjamSpec2TraitgjamTrimY

Dependencies:MASSRANNRcppRcppArmadillo

Generalized joint attribute modeling - gjam

James S. Clark

Rendered fromgjamVignette.Rmdusingknitr::rmarkdownon Nov 16 2024.

Last update: 2022-05-23
Started: 2016-01-04