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#' 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.
#'
#' The argument \code{N} is used to suppress computation of
#' abundance and average detection probability in calls to summarize the
#' \code{ds} and either \code{io.fi} or \code{trial.fi} for summaries of
#' \code{io} and \code{trial} objects respectively which are composed of a
#' \code{ds} model object and a mark-recapture model object. The corresponding
#' print function is called to print the summary results.
#'
#' @export
#' @param object a \code{ddf} model object
#' @param se if TRUE, computes standard errors
#' @param \dots unspecified and unused arguments for S3 consistency
#' @return list of extracted and summarized objects
#' @note This function is called by the generic function \code{summary} for any
#' \code{ddf} model object. Each function can be called directly by the
#' user, but it is typically safest to use the generic function
#' \code{summary} which calls the appropriate function based on the type of
#' \code{ddf} model.
#' @author Jeff Laake
#' @keywords utility
summary.trial <- function(object,se=TRUE,...){
# Uses: predict.trial, summary.ds, summary.trial.fi
model <- object
avgp <- function(model,pdot,...){return(pdot)}
n <- nrow(model$ds$ds$aux$ddfobj$xmat)
ans <- list(mr.summary = summary(model$mr,se=se,N=FALSE,fittedmodel=model),
ds.summary = summary(model$ds,se=se, N=FALSE),
Nhat = model$Nhat,
AIC = model$criterion,
average.p = n/model$Nhat)
# calculate se of average p
if(se){
se.obj <- calc.se.Np(model, avgp, n, ans$average.p)
ans$average.p.se <- se.obj$average.p.se
ans$Nhat.se <- se.obj$Nhat.se
}
ans$mono <- model$ds$aux$mono
ans$mono.strict <- model$ds$aux$mono.strict
class(ans) <- "summary.trial"
return(ans)
}
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