spAbundance

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 (2022) 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.

Last 30 days

This package has been downloaded 430 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 16 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 6,270 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Oct 08, 2024 with 62 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.