R/NCovered.rem.R

In DistanceDevelopment/mrds: Mark-Recapture Distance Sampling

# Compute abundance in covered region for trial model object
#
# par    - parameter values (used when computing derivatives wrt parameter uncertainty)
# model  - ddf model object
# group  - if TRUE computes group abundance and if FALSE individual abundance
#
# result - abundance estimate
NCovered.rem <- function(par, model, group=TRUE, ...){
  if(!is.null(par)){
    model$mr$mr$coefficients <- par[seq_along(model$mr$mr$coefficients)]
    model$ds$par <- par[(length(model$mr$mr$coefficients)+1):length(par)]
    model$ds$ds$aux$ddfobj <- assign.par(model$ds$ds$aux$ddfobj, model$ds$par)
    fitted <- predict(model, compute=TRUE, integrate=TRUE)$fitted
  }else{
    fitted <- model$fitted
  }

  if(!group){
    size <- model$data$size[model$data$observer==1 &
                            model$data$object %in%
                              as.numeric(names(model$fitted))]
    Nhat <- sum(compute.Nht(fitted,FALSE,size))
  }else{
    Nhat <- sum(compute.Nht(fitted,TRUE,size=NULL))
  }

  return(Nhat)
}