#' Print summary of distance detection function model object
#'
#' Provides a brief summary of data and fitted detection probability model
#' parameters, model selection criterion, and optionally abundance in the
#' covered (sampled) region and its standard error. What is printed depends
#' on the corresponding call to summary.
#'
#' @aliases print.summary.ds
#' @export
#' @param x a summary of \code{ddf} model object
#' @param \dots unspecified and unused arguments for S3 consistency
#' @return NULL
#' @author Jeff Laake
#' @seealso \code{\link{summary.ds}}
#' @keywords utility
print.summary.ds <- function (x, ...){
cat("\nSummary for ds object\n")
cat("Number of observations : ", x$n, "\n")
if(x$int.range){
cat("Distance range : ", x$left, " - ", x$width,
"(int.range set)\n")
}else{
cat("Distance range : ", x$left, " - ", x$width, "\n")
}
cat("AIC : ", x$aic, "\n")
cat("Optimisation : ", x$optimise, "\n")
cat("\nDetection function:\n", model.description(x), "\n")
cat("\nDetection function parameters", "\n")
cat("Scale coefficient(s):", "\n")
print(x$coeff$key.scale)
if(x$key %in% c("gamma", "hr", "th1", "th2")) {
cat("\nShape coefficient(s): ", "\n")
print(x$coeff$key.shape)
}
if(x$key == "tpn") {
cat("\nlog apex: ", "\n")
print(x$coeff$key.shape)
}
if (!is.null(x$coeff$adj.parm)) {
cat("\nAdjustment term coefficient(s): ", "\n")
print(x$coeff$adj.parm)
}
cat("\n")
if(x$mono & x$mono.strict){
cat("\nStrict monotonicity constraints were enforced.\n")
}else if(x$mono){
cat("\nMonotonicity constraints were enforced.\n")
}
if(!is.null(x$Nhat)){
parameters <- data.frame(Estimate=c(x$average.p, x$Nhat))
row.names(parameters) <- c("Average p", "N in covered region")
if(!is.null(x$average.p.se)){
parameters$SE <- c(x$average.p.se, x$Nhat.se)
parameters$CV <- parameters$SE/parameters$Estimate
}
}else{
parameters <- data.frame(Estimate=c(x$average.p))
row.names(parameters) <- c("Average p")
if(!is.null(x$average.p.se)){
parameters$SE <- c(x$average.p.se)
parameters$CV <- parameters$SE/parameters$Estimate
}
}
# for points include EDR info
if(x$transect == "point"){
parameters <- rbind(parameters,
"EDR"=c(
sqrt(parameters$Estimate[1]*(x$width-x$left)^2),
parameters$CV[1]/2 *
sqrt(parameters$Estimate[1]*(x$width-x$left)^2),
parameters$CV[1]/2))
}
print(parameters)
# Remind the user that monotonicity constraints were enforced
if(x$mono & x$mono.strict){
cat("\nStrict monotonicity constraints were enforced.\n")
}else if(x$mono){
cat("\nMonotonicity constraints were enforced.\n")
}
invisible()
}
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