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ghislainv/hSDM: hSDM CRAN release v1.4.1: Hierarchical Bayesian Species Distribution Models

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 13 May 2019 English Publisher:Zenodo
Authors: Ghislain Vieilledent; Matthieu Autier; Alan E. Gelfand; Jérôme Guélat; Marc Kéry; Andrew M. Latimer; Cory Merow; +5 Authors

doi: 10.5281/zenodo.2783949 , 10.5281/zenodo.8289500 , 10.5281/zenodo.8322378 , 10.5281/zenodo.7971368 , 10.5281/zenodo.594920

ghislainv/hSDM: hSDM CRAN release v1.4.1: Hierarchical Bayesian Species Distribution Models

Abstract

hSDM v1.4.1 for Hierarchical Bayesian Species Distribution Models Changes Use GSL for random sampling (issue #4) Convert package to use registration for C routines (issue #9) Install this release From CRAN or using the devtools::install_github() function in R: devtools::install_github(repo="ghislainv/hSDM", ref="v1.4.1")

Keywords

hierarchical Bayesian models, abundance, MCMC, spatial dependence, computational speed, imperfect detection, count data, C code, presence/absence data, Gibbs sampler, latente variable, probability of presence, species distribution models, Metropolis algorithm

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
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