#####################################################################
# (20190918) EJ
# Can we build a index of abundance based in genetics ?
# Demostration of impact of new index in stock assessment 
#####################################################################

library(FLa4a)
library(ggplotFL)
data(ple4)
data(ple4.index)
it <- 250

#====================================================================
# Default model, no index of recruitment
#====================================================================
fit0 <- sca(ple4, FLIndices(a=ple4.index))
stk0 <- ple4+simulate(fit0, it)

#====================================================================
# (flat) index of recruitment
#====================================================================
flq <- stock.n(ple4)[1]
flq[] <- rnorm(61, 5)
fit1 <- sca(ple4, FLIndices(a=ple4.index, b=FLIndex(index=flq, range=c(startf=0, endf=0))))
plot(FLStocks(Default=stk0, FlatIndex=ple4+simulate(fit1, it)))

#====================================================================
# (contrasted) index of recruitment
#====================================================================
set.seed(111)
ts.sim <- arima.sim(list(order = c(1,1,0), ar = 0.7), n = 61)[-1]
flq[] <- exp(scale(ts.sim))
flqv <- flq
flqv[] <- 0.3
fit2 <- sca(ple4, FLIndices(a=ple4.index, b=FLIndex(index=flq, index.var=flqv, range=c(startf=0, endf=0))))
plot(FLStocks(Default=stk0, FlatIndex=ple4+simulate(fit1, it) ,ContrastedIndex=ple4+simulate(fit2, it)))