Package: gjam 2.6.2

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

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gjam/json (API)

# Install 'gjam' in R:
install.packages('gjam', repos = c('https://jimclarkatduke.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

On CRAN:

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

17 exports 0.36 score 4 dependencies 1 mentions 144 scripts 723 downloads

Last updated 2 years agofrom:296c89707a. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 30 2024
R-4.5-win-x86_64NOTEAug 30 2024
R-4.5-linux-x86_64NOTEAug 30 2024
R-4.4-win-x86_64NOTEAug 30 2024
R-4.4-mac-x86_64NOTEAug 30 2024
R-4.4-mac-aarch64NOTEAug 30 2024
R-4.3-win-x86_64NOTEAug 30 2024
R-4.3-mac-x86_64NOTEAug 30 2024
R-4.3-mac-aarch64NOTEAug 30 2024

Exports:gjamgjamCensorYgjamConditionalParametersgjamDeZerogjamFillMissingTimesgjamIIEgjamIIEplotgjamOrdinationgjamPlotgjamPoints2GridgjamPredictgjamPriorTemplategjamReZerogjamSensitivitygjamSimDatagjamSpec2TraitgjamTrimY

Dependencies:MASSRANNRcppRcppArmadillo

Generalized joint attribute modeling - gjam

Rendered fromgjamVignette.Rmdusingknitr::rmarkdownon Aug 30 2024.

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