R/print.abund.R

In Rdistance: Distance-Sampling Analyses for Density and Abundance Estimation

#' @title Print abundance estimates
#' 
#' @description Print an object of class \code{c("abund","dfunc")} 
#' that is output by \code{abundEstim}.
#' 
#' @param x An object output by \code{abundEstim}.  This is a distance function object that 
#'   also contains abundance estimates, and has class \code{c("abund", "dfunc")}.
#'   
#' @param criterion A string specifying the criterion to print.
#' Must be one of "AICc" (the default), 
#' "AIC", or "BIC".  See \code{\link{AIC.dfunc}} for formulas. 
#' 
#' @param \dots Included for compatibility to other print methods.  Ignored here.
#' @details The default print method for class 'dfunc' is called, then the abundance estimates 
#'   contained in \code{obj} are printed.
#' @return No value is returned.
#' @author Trent McDonald, WEST Inc., \email{tmcdonald@west-inc.com}
#' @seealso \code{\link{dfuncEstim}}, \code{\link{abundEstim}}
#' @examples
#' # Load example sparrow data (line transect survey type)
#' data(sparrowDetectionData)
#' data(sparrowSiteData)
#' 
#' # Fit half-normal detection function
#' dfunc <- dfuncEstim(formula=dist~1,
#'                     detectionData=sparrowDetectionData,
#'                     likelihood="halfnorm", w.hi=100, pointSurvey=FALSE)
#' 
#' # Estimate abundance given a detection function
#' # Note, area=10000 converts to density per hectare (for distances measured in meters)
#' # Note, a person should do more than R=20 iterations
#' fit <- abundEstim(dfunc, detectionData=sparrowDetectionData,
#'                   siteData=sparrowSiteData, area=10000, R=20, ci=0.95,
#'                   plot.bs=TRUE, bySite=FALSE)
#' 
#' # Print results
#' print(fit)
#' fit
#' @keywords models
#' @export

print.abund <- function( x, criterion="AICc", ... ){
#
#   Print an object of class 'abund', which is class 'dfunc' with
#   an abundance estimate stored in it.
#

print.dfunc( x, criterion=criterion )

cat( paste( "Abundance estimate: ", format(x$n.hat), "; ",
        paste(x$alpha*100, "% CI=(", sep=""), format(x$ci[1]), 
        "to", format(x$ci[2]),
        ")\n"))
if(any(is.na(x$B))) cat(paste("CI based on", sum(!is.na(x$B)), "of", length(x$B), "successful bootstrap iterations\n"))        
cat( "\n" )

}