R/fit_colextfp.r

In oliviergimenez/occuHMM: Fit occupancy data with hidden Markov models

#' Fit dynamic occupancy models with false positives
#'
#' This function allows you to fit a dynamic occupancy model with false positives.
#' Data coding is as follows: 0 is for non-detection, 1 is for detection with no ambiguity, 2 is for detection with false positives possibly occurring.
#' @param data matrix of detections/non-detections
#' @param init vector of initial values
#' @param nb_surveys number of surveys/visits
#' @param nb_seasons number of seasons/years
#' @keywords maximum-likelihood
#' @export
#' @examples
#' vignette("colext_occuHMM")

fit_colextfp <- function(data,init,nb_surveys,nb_seasons){

# various quantities
J = nb_surveys
K = nb_seasons
nh <- dim(data)[1] # nb sites
eff = rep(1,nh) # nb sites with this particular history
garb = data[,1] # initial states
data = t(data) # transpose

# primary and secondary occasions
primary = seq(J,J*K,by=J)
secondary = 1:(J*K)

# run optim
binit <- runif(6)
tmpmin = optim(init,dev_colextfp,NULL,hessian=FALSE,data,eff,garb,nh,primary,secondary,method="BFGS",control=list(trace=1, REPORT=1))
tmpmin
}