ML_CS_store_params <-function(island_replicates,pars){
lambda_c <- factor()
mu <- factor()
K <- factor()
gamma <- factor()
lambda_a <- factor()
loglik <- factor()
df <- factor()
conv <- factor()
DAISIEMLSUM_CS <- data.frame(lambda_c,mu,K,gamma,lambda_a
,loglik,df,conv)
for (i in 1:length(island_replicates)){
DAISIEML_CS <- DAISIE::DAISIE_ML_CS(datalist=island_replicates[[i]], initparsopt = pars, ddmodel=0, idparsopt = 1:5, parsfix = NULL, idparsfix = NULL)
DAISIEMLSUM_CS <- rbind(DAISIEMLSUM_CS, DAISIEML_CS)
}
return(DAISIEMLSUM_CS)
}
islands_sim_MLE <- function(DAISIEMLSUM_CS){
islands_MLE = list()
for(rep in 1:(length(DAISIEMLSUM_CS)-1)){
lac <-DAISIEMLSUM_CS[rep,1]
mu <- DAISIEMLSUM_CS[rep,2]
k <- DAISIEMLSUM_CS[rep,3]
gam <- DAISIEMLSUM_CS[rep,4]
laa <- DAISIEMLSUM_CS[rep,5]
pars = c(lac,mu,k,gam,laa)
islands_MLE[[rep]] = DAISIE::DAISIE_sim(time=2,M=40,pars=pars,Tpars = NULL, replicates=10, divdepmodel = "CS")
}
samp_freq = length(islands_MLE[[rep]][[1]][[1]]$stt_all)
sum_endemics = list()
total = list()
for(rep in 1:(length(DAISIEMLSUM_CS)-1)){
sum_endemics[[rep]] <- islands_MLE[[rep]][[1]][[1]]$stt_all[samp_freq, "nA"] +
islands_MLE[[rep]][[1]][[1]]$stt_all[samp_freq, "nC"]
total[[rep]] <- islands_MLE[[rep]][[1]][[1]]$stt_all[samp_freq, "nA"] +
islands_MLE[[rep]][[1]][[1]]$stt_all[samp_freq, "nC"] +
islands_MLE[[rep]][[1]][[1]]$stt_all[samp_freq, "nI"]
}
}
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