library(R2admb)  ## requires version >=0.7.7
library(coda)
source("skate_ADMB_funs.R")

sessionInfo()

setup_admb()
skate.data <- readLines("../DATA/skate.dat")
writeLines(skate.data,"skate.dat")

if ('skate' %in% dir() ==FALSE) {compile_admb("skate", re=TRUE)} # compiles if file not already compiled (speeds up sims)
#if ('skate' %in% dir() ==FALSE) {compile_admb("skate", re=FALSE)} no random effects

st1 <- system.time(tfit_admb <- skate_ADMB_fit())["elapsed"]
st1 <- unname(st1)


ev <- try(eigen(solve(vcov(tfit_admb)))$value)
eratio <- if (inherits(ev,"try-error")) NA else min(ev)/max(ev)


results<- list(obj=-logLik(tfit_admb),  ## objective function/Neg log likelihood (NULL for MCMC)
                coef=coef(tfit_admb),  ## coefficients
                sd=stdEr(tfit_admb),
                confint.quad=confint(tfit_admb,method="quad",type="all"), # changed from extra
                time=c(fit=st1),
                terminfo=c(maxgrad=tfit_admb$maxgrad,eratio=eratio) ## MLE termination info
                )
save("results",file="fit.RData")
save("tfit_admb",file="tfit_admb.RData")