Package: hSDM 1.4.4
hSDM: Hierarchical Bayesian Species Distribution Models
User-friendly and fast set of functions for estimating parameters of hierarchical Bayesian species distribution models (Latimer and others 2006 <doi:10.1890/04-0609>). Such models allow interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results.
Authors:
hSDM_1.4.4.tar.gz
hSDM_1.4.4.tar.gz(r-4.5-noble)hSDM_1.4.4.tar.gz(r-4.4-noble)
hSDM_1.4.4.tgz(r-4.4-emscripten)hSDM_1.4.4.tgz(r-4.3-emscripten)
hSDM.pdf |hSDM.html✨
hSDM/json (API)
NEWS
# Install 'hSDM' in R: |
install.packages('hSDM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ghislainv/hsdm/issues
Pkgdown:https://ecology.ghislainv.fr
- altitude - Virtual altitudinal data
- cfr.env - Environmental data for South Africa's Cap Floristic Region
- data.Kery2010 - Count data for the Willow tit
- datacells.Latimer2006 - Data of presence-absence
- frogs - Counts of the number of frogs in a water body
- neighbors.Latimer2006 - Neighborhood data
- punc10 - Occurrence data for _Protea punctata_ Meisn. in the Cap Floristic Region
Last updated 1 years agofrom:23c17415d9. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 24 2024 |
R-4.5-linux-x86_64 | OK | Nov 24 2024 |
Exports:hSDM.binomialhSDM.binomial.iCARhSDM.NmixturehSDM.Nmixture.iCARhSDM.Nmixture.KhSDM.poissonhSDM.poisson.iCARhSDM.siteocchSDM.siteocc.iCARhSDM.ZIBhSDM.ZIB.iCARhSDM.ZIB.iCAR.alterationhSDM.ZIPhSDM.ZIP.iCARhSDM.ZIP.iCAR.alterationinv.logitlogit