Package: Rdistance 3.1.2

Rdistance: Distance-Sampling Analyses for Density and Abundance Estimation

Distance-sampling analyses (Buckland et al., (2015) <doi:10.1007/978-3-319-19219-2>) estimate density and abundance of survey targets (e.g., animals) when detection declines with distance. Distance-sampling is popular ecology, especially when survey targets are observed from aerial platforms (e.g., airplane or drone), surface vessels (e.g., boat or truck), or along walking transects. Both point and line transects can be analyzed. Outputs include overall (study area) density and abundance, effective sampling distances, and model fit statistics. A large suite of classical, parametric detection functions (e.g., half-normal, hazard rate) is included along with uncommon parametric functions (e.g., Gamma, negative exponential). Non-parametric smoothed distance functions are included. Measurement unit integrity is enforced via internal unit conversion. The help files and vignettes have been vetted by multiple authors and tested in workshop settings.

Authors:Trent McDonald [cre, aut], Jason Carlisle [aut], Aidan McDonald [aut], Ryan Nielson [ctb], Ben Augustine [ctb], James Griswald [ctb], Patrick McKann [ctb], Lacey Jeroue [ctb], Hoffman Abigail [ctb], Kleinsausser Michael [ctb], Joel Reynolds [ctb], Pham Quang [ctb], Earl Becker [ctb], Aaron Christ [ctb], Brook Russelland [ctb], Stefan Emmons [ctb], Will McDonald [ctb], Reid Olson [ctb]