Package: Rdistance
Type: Package
Title: Density and Abundance from Distance-Sampling Surveys
Version: 4.0.5
Date: 2025-04-10
Maintainer: Trent McDonald <trent@mcdonalddatasciences.com>
Authors@R: c(person("Trent", "McDonald", role=c("cre","aut"), email="trent@mcdonalddatasciences.com"), 
  person("Jason", "Carlisle", role="aut", email="jason.carlisle@wyo.gov"), 
  person("Aidan", "McDonald", role="aut", email="aidan@mcdcentral.org", comment="point transect methods"), 
  person("Ryan", "Nielson", role="ctb", comment="smoothed likelihood"), 
  person("Ben", "Augustine", role="ctb", comment="maximization method"), 
  person("James", "Griswald", role="ctb", comment="maximization method"), 
  person("Patrick", "McKann", role="ctb", comment="maximization method"), 
  person("Lacey", "Jeroue", role="ctb", comment="vignettes"), 
  person("Hoffman", "Abigail", role="ctb", comment="vignettes"), 
  person("Kleinsausser", "Michael", role="ctb", comment="vignettes"),
  person("Joel", "Reynolds", role="ctb", comment="Gamma likelihood"), 
  person("Pham", "Quang", role="ctb", comment="Gamma likelihood"), 
  person("Earl", "Becker", role="ctb", comment="Gamma likelihood"), 
  person("Aaron", "Christ", role="ctb", comment="Gamma likelihood"), 
  person("Brook", "Russelland", role="ctb", comment="Gamma likelihood"), 
  person("Stefan", "Emmons", role="ctb", comment="Automated tests"),
  person("Will", "McDonald", role="ctb", comment="Automated tests"),
  person("Reid", "Olson", role="ctb", comment="Automated tests and bug fixes"))
Description: Distance-sampling (<doi:10.1007/978-3-319-19219-2>) 
  estimates density and abundance of survey targets (e.g., animals) when 
  detection probability declines with distance. 
  Distance-sampling is popular in 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. 
  Distance-sampling includes line-transect studies that measure observation 
  distances as the closest approach of the sample route (transect) to the target 
  (i.e., perpendicular off-transect distance), and point-transect studies that 
  measure observation distances from stationary observers to 
  the target (i.e., radial distance). 
  The routines included here fit smooth (parametric) curves to 
  histograms of observation distances 
  and use those functions to compute effective sampling distances, density of 
  targets in the surveyed area, and abundance 
  of targets in a surrounding study area. Curve shapes include the 
  half-normal, hazard rate, and negative exponential functions.
  Physical measurement units are required and used throughout to 
  ensure density is reported correctly. The help files 
  are extensive and have been vetted by multiple authors. 
License: GNU General Public License
URL: https://github.com/tmcd82070/Rdistance/wiki
BugReports: https://github.com/tmcd82070/Rdistance/issues
Suggests: testthat (>= 3.0.0),
Depends: R (>= 4.1.0), units
Imports: graphics, stats, utils, crayon, withr, tidyr, dplyr, progress,
        tibble, tidyselect
RoxygenNote: 7.3.2
Encoding: UTF-8
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-04-10 17:04:59 UTC; trent
Author: Trent McDonald [cre, aut],
  Jason Carlisle [aut],
  Aidan McDonald [aut] (point transect methods),
  Ryan Nielson [ctb] (smoothed likelihood),
  Ben Augustine [ctb] (maximization method),
  James Griswald [ctb] (maximization method),
  Patrick McKann [ctb] (maximization method),
  Lacey Jeroue [ctb] (vignettes),
  Hoffman Abigail [ctb] (vignettes),
  Kleinsausser Michael [ctb] (vignettes),
  Joel Reynolds [ctb] (Gamma likelihood),
  Pham Quang [ctb] (Gamma likelihood),
  Earl Becker [ctb] (Gamma likelihood),
  Aaron Christ [ctb] (Gamma likelihood),
  Brook Russelland [ctb] (Gamma likelihood),
  Stefan Emmons [ctb] (Automated tests),
  Will McDonald [ctb] (Automated tests),
  Reid Olson [ctb] (Automated tests and bug fixes)
Repository: CRAN
Date/Publication: 2025-04-10 17:20:02 UTC
Built: R 4.6.0; ; 2025-08-18 15:12:44 UTC; unix
