Package: multiocc 0.2.0

multiocc: Fits Multivariate Spatio-Temporal Occupancy Model

Spatio-temporal multivariate occupancy models can handle multiple species in occupancy models. This method for fitting such models is described in Hepler and Erhardt (2021) "A spatiotemporal model for multivariate occupancy data" <https://onlinelibrary.wiley.com/doi/abs/10.1002/env.2657>.

Authors:Staci Hepler [aut, cre], Rob Erhardt [aut]

multiocc_0.2.0.tar.gz
multiocc_0.2.0.zip(r-4.5)multiocc_0.2.0.zip(r-4.4)multiocc_0.2.0.zip(r-4.3)
multiocc_0.2.0.tgz(r-4.4-any)multiocc_0.2.0.tgz(r-4.3-any)
multiocc_0.2.0.tar.gz(r-4.5-noble)multiocc_0.2.0.tar.gz(r-4.4-noble)
multiocc_0.2.0.tgz(r-4.4-emscripten)multiocc_0.2.0.tgz(r-4.3-emscripten)
multiocc.pdf |multiocc.html✨
multiocc/json (API)

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

Peer review:

Bug tracker:https://github.com/heplersa/multiocc/issues

Datasets:

On CRAN:

3.70 score 4 scripts 148 downloads 3 exports 14 dependencies

Last updated 1 years agofrom:0ab537e7c1. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winNOTENov 20 2024
R-4.5-linuxNOTENov 20 2024
R-4.4-winNOTENov 20 2024
R-4.4-macNOTENov 20 2024
R-4.3-winNOTENov 20 2024
R-4.3-macNOTENov 20 2024

Exports:GibbsSamplerMakeBasismultioccbuild

Dependencies:codadeldirgmminterplatticeMASSMatrixmvtnormRcppRcppEigensandwichtmvtnormtruncnormzoo

Introduction to the multiocc package

Rendered fromIntro_multiocc.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2023-05-25
Started: 2023-05-25