% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Rdistance-package.R
\docType{package}
\name{Rdistance-package}
\alias{Rdistance-package}
\alias{distance}
\alias{Rdistance}
\alias{point-transect}
\alias{line-transect}
\title{Rdistance - Distance Sampling Analyses for Abundance Estimation}
\description{
\code{Rdistance} contains functions and associated routines to analyze
distance-sampling data collected on point or line transects. 
Some of \code{Rdistance}'s features include:
\itemize{
   \item Accommodation of both point and line transect analyses 
    in one routine (\code{\link{dfuncEstim}}).
   \item Regression-like formula for inclusion of distance function
   covariates (\code{\link{dfuncEstim}}).
   \item Automatic bootstrap confidence intervals 
   (\code{\link{abundEstim}}).
   \item Availability of both study-area and site-level abundance
   estimates (\code{help("predict.dfunc")}).
   \item Classical, parametric distance functions
   (\code{\link{halfnorm.like}}, \code{\link{hazrate.like}}, 
   \code{\link{negexp.like}}), and
   expansion functions (\code{\link{cosine.expansion}}, 
   \code{\link{hermite.expansion}}, \code{\link{simple.expansion}}).
   
   
   \item Automated distance function fits and selection 
   \code{\link{autoDistSamp}}.
   
   \item \code{print}, \code{plot}, \code{predict}, \code{coef}, 
   and \code{summary} methods for distance function objects and 
   abundance classes.
}
}
\section{Background}{

Distance-sampling is a popular method for abundance estimation in
ecology. Line transect surveys are conducted by traversing
randomly placed transects in a study area with the objective of
sighting animals and estimating density or abundance.  Data collected
during line transect surveys consists of sighting records for
\emph{targets}, usually either individuals or groups of individuals.  Among
the collected data, off-transect distances are recorded or computed from
other information (see \code{\link{perpDists}}).  Off-transect distances 
are the perpendicular distances from the transect to the location of 
the initial sighting cue.
When groups are the target, the number of individuals in the group is
recorded.

Point transect surveys are similar except that observers stop one 
or more times along the transect to observe targets.  This is a 
popular method for avian surveys where detections are often auditory 
cues, but is also appropriate when automated detectors are placed along
a route.  Point transect surveys collect distances from the observer to 
the target and are sometimes called \emph{radial} distances.   


A fundamental characteristic of both line and point-based 
distance sampling analyses is that
probability of detecting a target declines as
off-transect or radial distances increase. Targets far from 
the observer are usually 
harder to detect than closer targets.  In most
classical line transect studies, targets on the transect (off-transect
distance = 0) are assume to be sighted with 100\% probability.  This
assumption allows estimation of the proportion of targets missed during the
survey, and thus it is possible to adjust the actual number of 
sighted targets for the proportion of targets missed. 
Some studies utilize two observers searching the same areas to
estimate the proportion of individuals missed and thereby eliminating the
assumption that all individuals on the line have been observed.
}

\section{Relationship to other software}{
 
A detailed comparison of
\code{Rdistance} to other options for distance sampling analysis (e.g.,
Program DISTANCE, R package \code{Distance}, and R package \code{unmarked})
is forthcoming.  While some of the functionality in \code{Rdistance} 
is not unique, our aim is to provide an easy-to-use, rigorous,
and flexible analysis option for distance-sampling data.  
We understand that beginning
users often need software that is both easy to use and easy to understand,
and that advanced users often require greater flexibility and customization.
Our aim is to meet the demands of both user groups.  \code{Rdistance} is
under active development, so please contact us with issues, feature
requests, etc. through the package's GitHub website
(\url{https://github.com/tmcd82070/Rdistance}).
}

\section{Data sets}{

 \code{Rdistance} contains four example data sets: two collected using 
line-transect methods (i.e., \code{\link{sparrowDetectionData}} and
\code{\link{sparrowSiteData}}) and two collected using point-transect
methods (i.e.,
\code{\link{thrasherDetectionData}} and \code{\link{thrasherSiteData}}).
}

\references{
Buckland, S.T., Anderson, D.R., Burnham, K.P. and Laake, J.L.
  1993. \emph{Distance Sampling: Estimating Abundance of Biological
  Populations}. Chapman and Hall, London.
}
\seealso{
Useful links:
\itemize{
  \item \url{https://mcdonalddatasciences.com/Rdistance.html}
  \item Report bugs at \url{https://github.com/tmcd82070/Rdistance/issues}
}

}
\author{
Main author and maintainer: Trent McDonald
<trent@mcdonalddatasciences.com>

Coauthors: Ryan Nielson, Jason Carlisle, and Aidan McDonald

Contributors: Ben Augustine, James Griswald, Joel Reynolds, Pham Quang, Earl
Becker, Aaron Christ, Brook Russelland, Patrick McKann, Lacey Jeroue, 
Abigail Hoffman, Michael Kleinsasser, and Ried Olson
}
\keyword{package}
