neonPredData

Land cover covariates (forest cover and grassland cover) extracted at 
a 1km resolution across the Disney Wildnerss Preserve for use in predicting density 
across the park. Land cover data come from USGS EROS.

datasets

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.

Jeffrey Doser

spAbundance

Univariate and Multivariate Spatial Modeling of Species
Abundance

Andrew Finley

neonPredData function

<code>neonPredData</code> is a data frame with four columns:
<code>forest</code>: proportion of forest cover within 1km radius.
<code>grass</code>: proportion of grassland cover within 1km radius.
<code>Easting</code>: the x coordinate of the point. The EPSG is 32617 (UTM Zone 17N).
<code>Northing</code>: the y coordinate of the point. The EPSG is 32617 (UTM Zone 17N).

neonPredData: Land cover covariates and coordinates at a 1ha resolution across Disney Wilderness Preserve

Description

Usage

Arguments

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