User manual

Science Manual – Using Video Images for Fisheries Monitoring 51
The addition of the IC improves the accuracy and precision of the estimates, but the
degree to which this happens will depend on the relative magnitudes of the three
parameters estimated. This model could be greatly improved by calibrating on a
longer time period, and including river flow as an explanatory variable for counter and
IC efficiency.
Robin Wyatt, 26 Mar 2007
The key part of the model in WinBUGS language is:
model{
fp.rate~dgamma(0.001,0.001)
counter.eff~dbeta(1,1)
vid.eff~dbeta(1,1)
#c.fp.rate <- cut(fp.rate)
#c.counter.eff <- cut(counter.eff)
#c.vid.eff <- cut(vid.eff)
c.fp.rate <- fp.rate
c.counter.eff <- counter.eff
c.vid.eff <- vid.eff
for (i in 1:4){
false.positive[i] ~ dpois(fp.rate)
count.fish[i] ~ dbin(counter.eff, fish[i])
vid[i] ~ dbin(vid.eff, fish[i])
}
#mu.p ~dnorm(0.0, 1.0E-5)
#sd.p ~ dunif(0,50)
#tau.p <- 1/(sd.p*sd.p)
#for (j in 1:4){
#Counter only
#p.fish[j] ~ dnorm(mu.p, tau.p)I(0,100)
#np[j] <- p.fish[j]*c.counter.eff+c.fp.rate
#npq[j] <- p.fish[j]*c.counter.eff*(1-c.counter.eff)+c.fp.rate
#p[j] <- 1-npq[j]/np[j]
#n[j] <- np[j]/p[j]
#counter[j] ~ dbin(p[j],n[j])
#Counter + IC
#p.fish[j] ~ dnorm(mu.p, tau.p)I(0,100)
#np[j] <- p.fish[j]*c.counter.eff+c.fp.rate
#npq[j] <- p.fish[j]*c.counter.eff*(1-c.counter.eff)+c.fp.rate
#p[j] <- 1-npq[j]/np[j]
#n[j] <- np[j]/p[j]
#counter[j] ~ dbin(p[j],n[j])
#vid2[j] ~ dbin(c.vid.eff, p.fish[j])
#}
}
#Data
list(
fish=c(15, 17, 15, 7),