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hierarchicalDS  

Functions to Perform Hierarchical Analysis of Distance Sampling Data
View on CRAN: Click here


Download and install hierarchicalDS package within the R console
Install from CRAN:
install.packages("hierarchicalDS")

Install from Github:
library("remotes")
install_github("cran/hierarchicalDS")

Install by package version:
library("remotes")
install_version("hierarchicalDS", "3.0")



Attach the package and use:
library("hierarchicalDS")
Maintained by
Paul B Conn
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-07-12
Latest Update: 2023-08-08
Description:
Functions for performing hierarchical analysis of distancesampling data with ability to use an areal spatial ICAR model ontop of user supplied covariates to get at variation in abundanceintensity. The detection model can be specified as a function ofobserver and individual covariates where a parametric model issupposed for the population level distribution of covariate values.The model uses data augmentation and a reversible jump MCMCalgorithm to sample animals that were never observed. Alsoincluded is the ability to include point independence increasingcorrelation multiple observers observations as a function ofdistance with independence assumed for distance0 or firstdistance bin as well as the ability to model speciesmisclassification rates using a multinomial logit formulation on datafrom double observers. There is also the the ability toinclude zero inflation but this is only recommended for cases wheresample sizes and spatial coverage of the survey are high.
How to cite:
Paul B Conn (2012). hierarchicalDS: Functions to Perform Hierarchical Analysis of Distance Sampling Data. R package version 3.0, https://cran.r-project.org/web/packages/hierarchicalDS
Previous versions and publish date:
1.0 (2012-07-12 19:46), 2.01 (2012-09-28 18:48), 2.9 (2014-11-26 08:09), 3.0 (2019-07-02 20:10)
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