gistfile1.txt

# Assume just the first 16 parameters vary, but can do the same thing.
df <-
  data.frame(
    ad.surv.intercept=rep(0.0002516054, 16 * 2),
    ad.surv.temp=0.1702,
    ad.surv.pack=-0.1654,
    disp.intercept=0.0064262,
    disp.pack.size=0.10594,
    #IBI.average=10.81
    #IBI.temp=1.02
    pup.intercept=0.87515,
    pup.pack.size=0.04574,
    juv.surv.intercept=18.61131,
    juv.surv.temp=-0.70572,
    juv.surv.litter=0.5482,
    IBI.intercept=-17.25578,
    IBI.tempcoef=0.91565,
    IBI.pups=0.51976,
    #sets my mean temperature (change temp)
    meantemp=28.22864,
    #the actual mean temperature at present
    actual.meantemp=28.22864,
    number.of.packs=9
  )


for(i in 1:(nrow(df) / 2)){
  df[i, i] <- 0.99 * df[i, i]
}
for(i in ((nrow(df) / 2) + 1) : nrow(df)){
  df[i, i - nrow(df) / 2] <- 0.99 * df[i, i - nrow(df) / 2]
}

#for 2 iterations (guessing you want 1000 because it's stochastic)
its <- 2
df_big <- do.call(rbind, replicate(its, df, simplify = FALSE))




tic()
results <- 
  lapply(1:nrow(df_big), function(x) 
    results = run_simulation(df_big[x, 1],
                             df_big[x, 2],
                             ad.surv.pack,disp.intercept,disp.pack.size,IBI.intercept,IBI.tempcoef,IBI.pups,
                             pup.intercept,pup.pack.size,juv.surv.intercept,juv.surv.temp,juv.surv.litter,
                             meantemp,actual.meantemp,number.of.packs,n.steps,repeats, burntime)
  )
toc()