Package: hierarchicalDS
Maintainer: Paul B Conn <paul.conn@noaa.gov>
License: Unlimited
Title: Functions to Perform Hierarchical Analysis of Distance Sampling
        Data
Type: Package
LazyLoad: yes
Author: P.B. Conn \email{paul.conn@@noaa.gov}
Description: Functions for performing hierarchical analysis of distance
    sampling data, with ability to use an areal spatial ICAR model on
    top of user supplied covariates to get at variation in abundance
    intensity.  The detection model can be specified as a function of
    observer and individual covariates, where a parametric model is
    supposed for the population level distribution of covariate values.
    The model uses data augmentation and a reversible jump MCMC
    algorithm to sample animals that were never observed.  Also
    included is the ability to include point independence (increasing
    correlation multiple observer's observations as a function of
    distance, with independence assumed for distance=0 or first
    distance bin), as well as the ability to model species
    misclassification rates using a multinomial logit formulation on data
    from double observers.  There is also the the ability to
    include zero inflation, but this is only recommended for cases where
    sample sizes and spatial coverage of the survey are high.
Version: 3.0
Imports: truncnorm, mvtnorm, Matrix, coda, xtable, mc2d, ggplot2,
        rgeos, MCMCpack
Date: 2019-07-01
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-02 16:49:11 UTC; paul.conn
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2019-07-02 18:10:03 UTC
Built: R 4.1.0; ; 2020-08-03 12:13:25 UTC; windows
