Installation
About
Fits single-species (univariate) and multi-species (multivariate) non-spatial and spatial abundance models in a Bayesian framework using Markov Chain Monte Carlo (MCMC). Spatial models are fit using Nearest Neighbor Gaussian Processes (NNGPs). Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) doi:10.1080/01621459.2015.1044091 and Finley, Datta, and Banerjee (2020) doi:10.18637/jss.v103.i05. Fits single-species and multi-species spatial and non-spatial versions of generalized linear mixed models (Gaussian, Poisson, Negative Binomial), N-mixture models (Royle 2004 doi:10.1111/j.0006-341X.2004.00142.x) and hierarchical distance sampling models (Royle, Dawson, Bates (2004) doi:10.1890/03-3127). Multi-species spatial models are fit using a spatial factor modeling approach with NNGPs for computational efficiency.
Citation | spAbundance citation info |
www.jeffdoser.com/files/spabundance-web | |
Bug report | File report |
Key Metrics
Downloads
Yesterday | 20 0% |
Last 7 days | 165 +15% |
Last 30 days | 493 +24% |
Last 90 days | 1.333 -19% |
Last 365 days | 4.351 |
Maintainer
Maintainer | Jeffrey Doser |