Detection data from American black bears and code used in "Evaluating spatially explicit density estimates of unmarked wildlife detected by remote cameras" published in the Journal of Applied Ecology (Evans & Rittenhouse 2018). Unmarked detection data was collected using remote cameras in northwest Connecticut in 2014, and individual detection data was determined from unique genotypes obtained from non-invasive hair snares constructed at camera sampling locations. EN14.rds contains detection data as an R list: $y (num): J (sites) x K (occasions) matrix containing detection counts $X (int): 2 x J matrix of site coordinates $xlims (num): bounding x-coordinates $ylims (num): bounding y-coordinates $M (int): upper bound for super population of individuals $nTraps (int): number of sampling sites (J) $nReps (int): number of MCMC interations $forest (num): vector of site-specific covariates $mark (int): K x I matrix storing site numbers at which individual (i) was detected on occasion k FullModel.R provides functions used to fit constant density models to unmarked detections incorporating covariates of detection probability. partialID.R provides functions and code used to estimate density from mixtures of marked and unmarked detection data VariableDensity.R provides functions and code used to fit variable density models to unmarked detection data incorporating spatial covariates of density.

{"references": ["Chandler, SC & Royle, JA (2013). Spatially explicit models for inference about density in unmarked or partially marked populations. Annals of Applied Statistics, 7(2), 936\u2013954."]}

Version 1.0.1 includes previously omitted 'Full_Model.R' script file.