R/growthModelFunctions_Code.R
In bletcher/linkedModels: Link movement, growth, and survival models
library(nimble)
codeSpp <- list()
## BKT
codeSpp[[1]] <- nimbleCode({
##
for( i in 1:nEvalRows ) {
##
mu[ evalRows[i] ] <- lengthDATA[ evalRows[i] ] + ( gr[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
lengthDATA[ evalRows[i] + 1 ] ~ dnorm( mu[ evalRows[i] ],
sd = expectedGRSigma[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
##
gr[ evalRows[i] ] <-
grInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
# grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
# grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# #
# # grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[ evalRows[i] ] +
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[ evalRows[i] ]^2 +
# # grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd2[evalRows[i]] +
# grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
# # #
# grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
# grBetaBNT[3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# # #
# grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# # # grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
###################################################################
grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 +
grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[ evalRows[i] ]^2 +
# grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 * flowStd[ evalRows[i] ]^2 +
grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
grBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]]^2 +
# #
grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# #
grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grIndRE[ ind[evalRows[i]] ]
##
log( expectedGRSigma[ evalRows[i] ] ) <- #grSigma
sigmaInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# poor mixing when included sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
sigmaBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
sigmaBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]]
}
##
for( s in 1:nSeasons ) {
grIntMu[ s ] ~ dnorm(0,sd = 30) #changed from 0.001
grIntSigma[ s ] ~ dunif(0,10)
##
sigmaIntMu[ s ] ~ dnorm(0,sd = 30)
sigmaIntSigma[ s ] ~ dunif(0,10)
##
for( b in 1:nBetas ) { ############# Beta ##############################################################################
grBetaMu[ b,s ] ~ dnorm(0,sd = 30)
grBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( b in 1:nBetasSigma ) { ############# Beta ##############################################################################
sigmaBetaMu[ b,s ] ~ dnorm(0,sd = 30)
sigmaBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( yoy in 1:2 ) {
for( r in 1:nRivers ) {
grInt[ yoy,s,r ] ~ dnorm( grIntMu[ s ], grIntSigma[ s ] )
sigmaInt[ yoy,s,r ] ~ dnorm( sigmaIntMu[ s ], sigmaIntSigma[ s ] ) #T(0,) #dunif(0,100)
##
for( b in 1:nBetas ) { ############# Beta ##################################################################################
grBeta[ b,yoy,s,r ] ~ dnorm( grBetaMu[ b,s ], grBetaSigma[ b,s ] )
}
for( b in 1:nBetasSigma ) { ############# Beta ##################################################################################
sigmaBeta[ b,yoy,s,r ] ~ dnorm( sigmaBetaMu[ b,s ], sigmaBetaSigma[ b,s ] )
}
}
}
}
# #nATS priors
for( b in 1:nBetasATS ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaATS[ b,yoy,s,1 ] ~ dnorm( grBetaATSMu[ b,s ], sd = grBetaATSSigma[ b,s ] )
grBetaATS[ b,yoy,s,2 ] <- 0
grBetaATS[ b,yoy,s,3 ] <- 0
grBetaATS[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasATS ) {
for( s in 1:nSeasons ) {
grBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaATSSigma[ b,s ] ~ dunif( 0,100 )
}
}
#nBNT priors
for( b in 1:nBetasBNT ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaBNT[ b,yoy,s,1 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
grBetaBNT[ b,yoy,s,2 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
grBetaBNT[ b,yoy,s,3 ] <- 0
grBetaBNT[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasBNT ) {
for( s in 1:nSeasons ) {
grBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
}
}
##
# for( yoy in 1:2 ) {
# for( s in 1:nSeasons ) {
# grATSOffset[ yoy,s ] ~ dnorm( 0, sd = 30 )
# }
# }
for(ii in 1:nEvalRows) {
lengthExp[ evalRows[ii] + 1 ] <- lengthDATA[ evalRows[ii] ] + gr[ evalRows[ii] ] * sampleInterval[ evalRows[ii] ]
}
############ standardized length for sizeBetas
for( i in 1:(nEvalRows) ){
lengthStd[ evalRows[i] ] <- ( lengthDATA[ evalRows[i] ] - lengthMean ) / lengthSD
}
##
# including this messes up predictions
# for(ii in 1:nFirstObsRows) {
# lengthExp[ firstObsRows[ii] ] <- lengthDATA[ firstObsRows[ii] ]
# }
##
# individual random effect on gr
# for(iii in 1:nInd) {
# grIndRE[ iii ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
#
# }
# ##
# sigmaIndRE ~ dunif(0.01,0.5)
# ## individual random effect on gr
for(iii in 1:nMoreThanOneInterval) {
grIndRE[ moreThanOneInterval[iii] ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
}
for(iii in 1:nExactlyOneInterval) {
grIndRE[ exactlyOneInterval[iii] ] <- 0
}
##
sigmaIndRE ~ dunif(0.01,0.5)
})
## BNT
codeSpp[[2]] <- nimbleCode({
##
for( i in 1:nEvalRows ) {
##
mu[ evalRows[i] ] <- lengthDATA[ evalRows[i] ] + ( gr[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
lengthDATA[ evalRows[i] + 1 ] ~ dnorm( mu[ evalRows[i] ],
sd = expectedGRSigma[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
##
gr[ evalRows[i] ] <-
grInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
# grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
# grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
#
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
#
# grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
# grBetaBNT[3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 +
grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[ evalRows[i] ]^2 +
# grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 * flowStd[ evalRows[i] ]^2 +
grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
grBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]]^2 +
# #
grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# #
grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grIndRE[ ind[evalRows[i]] ]
##
log( expectedGRSigma[ evalRows[i] ] ) <- #grSigma
sigmaInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
sigmaBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
sigmaBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]]
# sigmaBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# sigmaBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# sigmaBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]] ] * cATSStd[evalRows[i]]
# sigmaBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * tempStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * tempStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * tempStd[evalRows[i]] * ATS01DATA[evalRows[i]] +
# sigmaBeta[ 9, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# sigmaBeta[10, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * flowStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[11, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * flowStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[12, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * flowStd[evalRows[i]] * ATS01DATA[evalRows[i]]
}
##
for( s in 1:nSeasons ) {
grIntMu[ s ] ~ dnorm(0,sd = 30) #changed from 0.001
grIntSigma[ s ] ~ dunif(0,10)
##
sigmaIntMu[ s ] ~ dnorm(0,sd = 30)
sigmaIntSigma[ s ] ~ dunif(0,10)
##
for( b in 1:nBetas ) { ############# Beta ##############################################################################
grBetaMu[ b,s ] ~ dnorm(0,sd = 30)
grBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( b in 1:nBetasSigma ) { ############# Beta ##############################################################################
sigmaBetaMu[ b,s ] ~ dnorm(0,sd = 30)
sigmaBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( yoy in 1:2 ) {
for( r in 1:nRivers ) {
grInt[ yoy,s,r ] ~ dnorm( grIntMu[ s ], sd = grIntSigma[ s ] )
sigmaInt[ yoy,s,r ] ~ dnorm( sigmaIntMu[ s ], sd = sigmaIntSigma[ s ] ) #T(0,) #dunif(0,100)
##
for( b in 1:nBetas ) { ############# Beta ##################################################################################
grBeta[ b,yoy,s,r ] ~ dnorm( grBetaMu[ b,s ], sd = grBetaSigma[ b,s ] )
}
for( b in 1:nBetasSigma ) { ############# Beta ##################################################################################
sigmaBeta[ b,yoy,s,r ] ~ dnorm( sigmaBetaMu[ b,s ], sd = sigmaBetaSigma[ b,s ] )
}
}
}
}
# nATS priors
for( b in 1:nBetasATS ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaATS[ b,yoy,s,1 ] ~ dnorm( grBetaATSMu[ b,s ], sd = grBetaATSSigma[ b,s ] )
grBetaATS[ b,yoy,s,2 ] <- 0
# sigmaBetaATS[ b,yoy,s ] ~ dnorm( sigmaBetaATSMu[ b,s ], sd = sigmaBetaATSSigma[ b,s ] )
}
}
}
for( b in 1:nBetasATS ) {
for( s in 1:nSeasons ) {
grBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaATSSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaATSSigma[ b,s ] ~ dunif( 0,100 )
}
}
#nBNT priors
for( b in 1:nBetasBNT ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaBNT[ b,yoy,s,1 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
grBetaBNT[ b,yoy,s,2 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
# grBetaBNT[ b,yoy,s,3 ] <- 0
# grBetaBNT[ b,yoy,s,4 ] <- 0
# sigmaBetaBNT[ b,yoy,s,1 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
# sigmaBetaBNT[ b,yoy,s,2 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
# sigmaBetaBNT[ b,yoy,s,3 ] <- 0
# sigmaBetaBNT[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasBNT ) {
for( s in 1:nSeasons ) {
grBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
}
}
##
# for( yoy in 1:2 ) {
# for( s in 1:nSeasons ) {
# grATSOffset[ yoy,s ] ~ dnorm( 0, sd = 30 )
# }
# }
for(ii in 1:nEvalRows) {
lengthExp[ evalRows[ii] + 1 ] <- lengthDATA[ evalRows[ii] ] + gr[ evalRows[ii] ] * sampleInterval[ evalRows[ii] ]
}
############ standardized length for sizeBetas
for( i in 1:(nEvalRows) ){
lengthStd[ evalRows[i] ] <- ( lengthDATA[ evalRows[i] ] - lengthMean ) / lengthSD
}
##
# including this messes up predictions
# for(ii in 1:nFirstObsRows) {
# lengthExp[ firstObsRows[ii] ] <- lengthDATA[ firstObsRows[ii] ]
# }
##
# ## individual random effect on gr
# for(iii in 1:nInd) {
# grIndRE[ iii ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)# )
#
# }
# ##
# sigmaIndRE ~ dunif(0.01,0.5)
# ## individual random effect on gr
for(iii in 1:nMoreThanOneInterval) {
grIndRE[ moreThanOneInterval[iii] ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
}
for(iii in 1:nExactlyOneInterval) {
grIndRE[ exactlyOneInterval[iii] ] <- 0
}
##
sigmaIndRE ~ dunif(0.01,0.5)
})
## ATS
codeSpp[[3]] <- nimbleCode({
##
for( i in 1:nEvalRows ) {
##
mu[ evalRows[i] ] <- lengthDATA[ evalRows[i] ] + ( gr[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
lengthDATA[ evalRows[i] + 1 ] ~ dnorm( mu[ evalRows[i] ],
sd = expectedGRSigma[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
##
gr[ evalRows[i] ] <-
grInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
# grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
# grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
# # grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd2[evalRows[i]] +
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd2[evalRows[i]] +
# grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 +
grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[ evalRows[i] ]^2 +
# grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 * flowStd[ evalRows[i] ]^2 +
grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
grBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]]^2 +
# #
grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# #
grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grIndRE[ ind[evalRows[i]] ]
##
log( expectedGRSigma[ evalRows[i] ] ) <- #grSigma
sigmaInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
sigmaBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
sigmaBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]]
# sigmaBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# sigmaBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# sigmaBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]] ] * cATSStd[evalRows[i]]
# sigmaBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * tempStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * tempStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * tempStd[evalRows[i]] * ATS01DATA[evalRows[i]] +
# sigmaBeta[ 9, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# sigmaBeta[10, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * flowStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[11, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * flowStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[12, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * flowStd[evalRows[i]] * ATS01DATA[evalRows[i]]
}
##
for( s in 1:nSeasons ) {
grIntMu[ s ] ~ dnorm(0,sd = 30) #changed from 0.001
grIntSigma[ s ] ~ dunif(0,10)
##
sigmaIntMu[ s ] ~ dnorm(0,sd = 30)
sigmaIntSigma[ s ] ~ dunif(0,10)
##
for( b in 1:nBetas ) { ############# Beta ##############################################################################
grBetaMu[ b,s ] ~ dnorm(0,sd = 30)
grBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( b in 1:nBetasSigma ) { ############# Beta ##############################################################################
sigmaBetaMu[ b,s ] ~ dnorm(0,sd = 30)
sigmaBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( yoy in 1:2 ) {
for( r in 1:nRivers ) {
grInt[ yoy,s,r ] ~ dnorm( grIntMu[ s ], sd = grIntSigma[ s ] )
sigmaInt[ yoy,s,r ] ~ dnorm( sigmaIntMu[ s ], sd = sigmaIntSigma[ s ] ) #T(0,) #dunif(0,100)
##
for( b in 1:nBetas ) { ############# Beta ##################################################################################
grBeta[ b,yoy,s,r ] ~ dnorm( grBetaMu[ b,s ], sd = grBetaSigma[ b,s ] )
}
for( b in 1:nBetasSigma ) { ############# Beta ##################################################################################
sigmaBeta[ b,yoy,s,r ] ~ dnorm( sigmaBetaMu[ b,s ], sd = sigmaBetaSigma[ b,s ] )
}
}
}
}
# nATS priors
for( b in 1:nBetasATS ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaATS[ b,yoy,s,1 ] ~ dnorm( grBetaATSMu[ b,s ], sd = grBetaATSSigma[ b,s ] )
# sigmaBetaATS[ b,yoy,s ] ~ dnorm( sigmaBetaATSMu[ b,s ], sd = sigmaBetaATSSigma[ b,s ] )
}
}
}
for( b in 1:nBetasATS ) {
for( s in 1:nSeasons ) {
grBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaATSSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaATSSigma[ b,s ] ~ dunif( 0,100 )
}
}
#nBNT priors
for( b in 1:nBetasBNT ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaBNT[ b,yoy,s,1 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
#grBetaBNT[ b,yoy,s,2 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
# grBetaBNT[ b,yoy,s,3 ] <- 0
# grBetaBNT[ b,yoy,s,4 ] <- 0
# sigmaBetaBNT[ b,yoy,s,1 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
#sigmaBetaBNT[ b,yoy,s,2 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
# sigmaBetaBNT[ b,yoy,s,3 ] <- 0
# sigmaBetaBNT[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasBNT ) {
for( s in 1:nSeasons ) {
grBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
}
}
##
# for( yoy in 1:2 ) {
# for( s in 1:nSeasons ) {
# grATSOffset[ yoy,s ] ~ dnorm( 0, sd = 30 )
# }
# }
for(ii in 1:nEvalRows) {
lengthExp[ evalRows[ii] + 1 ] <- lengthDATA[ evalRows[ii] ] + gr[ evalRows[ii] ] * sampleInterval[ evalRows[ii] ]
}
############ standardized length for sizeBetas
for( i in 1:(nEvalRows) ){
lengthStd[ evalRows[i] ] <- ( lengthDATA[ evalRows[i] ] - lengthMean ) / lengthSD
}
##
# including this messes up predictions
# for(ii in 1:nFirstObsRows) {
# lengthExp[ firstObsRows[ii] ] <- lengthDATA[ firstObsRows[ii] ]
# }
##
## individual random effect on gr
# for(iii in 1:nInd) {
# grIndRE[ iii ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)# )
#
# }
# ##
# sigmaIndRE ~ dunif(0.001,0.5)
for(iii in 1:nMoreThanOneInterval) {
grIndRE[ moreThanOneInterval[iii] ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
}
for(iii in 1:nExactlyOneInterval) {
grIndRE[ exactlyOneInterval[iii] ] <- 0
}
##
sigmaIndRE ~ dunif(0.01,0.5)
})
bletcher/linkedModels documentation built on May 14, 2019, 5:24 p.m.
R Package Documentation
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library(nimble)
codeSpp <- list()
## BKT
codeSpp[[1]] <- nimbleCode({
##
for( i in 1:nEvalRows ) {
##
mu[ evalRows[i] ] <- lengthDATA[ evalRows[i] ] + ( gr[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
lengthDATA[ evalRows[i] + 1 ] ~ dnorm( mu[ evalRows[i] ],
sd = expectedGRSigma[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
##
gr[ evalRows[i] ] <-
grInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
# grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
# grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# #
# # grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[ evalRows[i] ] +
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[ evalRows[i] ]^2 +
# # grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd2[evalRows[i]] +
# grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
# # #
# grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
# grBetaBNT[3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# # #
# grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# # # grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
###################################################################
grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 +
grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[ evalRows[i] ]^2 +
# grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 * flowStd[ evalRows[i] ]^2 +
grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
grBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]]^2 +
# #
grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# #
grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grIndRE[ ind[evalRows[i]] ]
##
log( expectedGRSigma[ evalRows[i] ] ) <- #grSigma
sigmaInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# poor mixing when included sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
sigmaBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
sigmaBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]]
}
##
for( s in 1:nSeasons ) {
grIntMu[ s ] ~ dnorm(0,sd = 30) #changed from 0.001
grIntSigma[ s ] ~ dunif(0,10)
##
sigmaIntMu[ s ] ~ dnorm(0,sd = 30)
sigmaIntSigma[ s ] ~ dunif(0,10)
##
for( b in 1:nBetas ) { ############# Beta ##############################################################################
grBetaMu[ b,s ] ~ dnorm(0,sd = 30)
grBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( b in 1:nBetasSigma ) { ############# Beta ##############################################################################
sigmaBetaMu[ b,s ] ~ dnorm(0,sd = 30)
sigmaBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( yoy in 1:2 ) {
for( r in 1:nRivers ) {
grInt[ yoy,s,r ] ~ dnorm( grIntMu[ s ], grIntSigma[ s ] )
sigmaInt[ yoy,s,r ] ~ dnorm( sigmaIntMu[ s ], sigmaIntSigma[ s ] ) #T(0,) #dunif(0,100)
##
for( b in 1:nBetas ) { ############# Beta ##################################################################################
grBeta[ b,yoy,s,r ] ~ dnorm( grBetaMu[ b,s ], grBetaSigma[ b,s ] )
}
for( b in 1:nBetasSigma ) { ############# Beta ##################################################################################
sigmaBeta[ b,yoy,s,r ] ~ dnorm( sigmaBetaMu[ b,s ], sigmaBetaSigma[ b,s ] )
}
}
}
}
# #nATS priors
for( b in 1:nBetasATS ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaATS[ b,yoy,s,1 ] ~ dnorm( grBetaATSMu[ b,s ], sd = grBetaATSSigma[ b,s ] )
grBetaATS[ b,yoy,s,2 ] <- 0
grBetaATS[ b,yoy,s,3 ] <- 0
grBetaATS[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasATS ) {
for( s in 1:nSeasons ) {
grBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaATSSigma[ b,s ] ~ dunif( 0,100 )
}
}
#nBNT priors
for( b in 1:nBetasBNT ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaBNT[ b,yoy,s,1 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
grBetaBNT[ b,yoy,s,2 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
grBetaBNT[ b,yoy,s,3 ] <- 0
grBetaBNT[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasBNT ) {
for( s in 1:nSeasons ) {
grBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
}
}
##
# for( yoy in 1:2 ) {
# for( s in 1:nSeasons ) {
# grATSOffset[ yoy,s ] ~ dnorm( 0, sd = 30 )
# }
# }
for(ii in 1:nEvalRows) {
lengthExp[ evalRows[ii] + 1 ] <- lengthDATA[ evalRows[ii] ] + gr[ evalRows[ii] ] * sampleInterval[ evalRows[ii] ]
}
############ standardized length for sizeBetas
for( i in 1:(nEvalRows) ){
lengthStd[ evalRows[i] ] <- ( lengthDATA[ evalRows[i] ] - lengthMean ) / lengthSD
}
##
# including this messes up predictions
# for(ii in 1:nFirstObsRows) {
# lengthExp[ firstObsRows[ii] ] <- lengthDATA[ firstObsRows[ii] ]
# }
##
# individual random effect on gr
# for(iii in 1:nInd) {
# grIndRE[ iii ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
#
# }
# ##
# sigmaIndRE ~ dunif(0.01,0.5)
# ## individual random effect on gr
for(iii in 1:nMoreThanOneInterval) {
grIndRE[ moreThanOneInterval[iii] ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
}
for(iii in 1:nExactlyOneInterval) {
grIndRE[ exactlyOneInterval[iii] ] <- 0
}
##
sigmaIndRE ~ dunif(0.01,0.5)
})
## BNT
codeSpp[[2]] <- nimbleCode({
##
for( i in 1:nEvalRows ) {
##
mu[ evalRows[i] ] <- lengthDATA[ evalRows[i] ] + ( gr[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
lengthDATA[ evalRows[i] + 1 ] ~ dnorm( mu[ evalRows[i] ],
sd = expectedGRSigma[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
##
gr[ evalRows[i] ] <-
grInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
# grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
# grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
#
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
#
# grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
# grBetaBNT[3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 +
grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[ evalRows[i] ]^2 +
# grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 * flowStd[ evalRows[i] ]^2 +
grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
grBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]]^2 +
# #
grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# #
grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grIndRE[ ind[evalRows[i]] ]
##
log( expectedGRSigma[ evalRows[i] ] ) <- #grSigma
sigmaInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
sigmaBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
sigmaBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]]
# sigmaBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# sigmaBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# sigmaBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]] ] * cATSStd[evalRows[i]]
# sigmaBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * tempStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * tempStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * tempStd[evalRows[i]] * ATS01DATA[evalRows[i]] +
# sigmaBeta[ 9, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# sigmaBeta[10, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * flowStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[11, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * flowStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[12, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * flowStd[evalRows[i]] * ATS01DATA[evalRows[i]]
}
##
for( s in 1:nSeasons ) {
grIntMu[ s ] ~ dnorm(0,sd = 30) #changed from 0.001
grIntSigma[ s ] ~ dunif(0,10)
##
sigmaIntMu[ s ] ~ dnorm(0,sd = 30)
sigmaIntSigma[ s ] ~ dunif(0,10)
##
for( b in 1:nBetas ) { ############# Beta ##############################################################################
grBetaMu[ b,s ] ~ dnorm(0,sd = 30)
grBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( b in 1:nBetasSigma ) { ############# Beta ##############################################################################
sigmaBetaMu[ b,s ] ~ dnorm(0,sd = 30)
sigmaBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( yoy in 1:2 ) {
for( r in 1:nRivers ) {
grInt[ yoy,s,r ] ~ dnorm( grIntMu[ s ], sd = grIntSigma[ s ] )
sigmaInt[ yoy,s,r ] ~ dnorm( sigmaIntMu[ s ], sd = sigmaIntSigma[ s ] ) #T(0,) #dunif(0,100)
##
for( b in 1:nBetas ) { ############# Beta ##################################################################################
grBeta[ b,yoy,s,r ] ~ dnorm( grBetaMu[ b,s ], sd = grBetaSigma[ b,s ] )
}
for( b in 1:nBetasSigma ) { ############# Beta ##################################################################################
sigmaBeta[ b,yoy,s,r ] ~ dnorm( sigmaBetaMu[ b,s ], sd = sigmaBetaSigma[ b,s ] )
}
}
}
}
# nATS priors
for( b in 1:nBetasATS ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaATS[ b,yoy,s,1 ] ~ dnorm( grBetaATSMu[ b,s ], sd = grBetaATSSigma[ b,s ] )
grBetaATS[ b,yoy,s,2 ] <- 0
# sigmaBetaATS[ b,yoy,s ] ~ dnorm( sigmaBetaATSMu[ b,s ], sd = sigmaBetaATSSigma[ b,s ] )
}
}
}
for( b in 1:nBetasATS ) {
for( s in 1:nSeasons ) {
grBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaATSSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaATSSigma[ b,s ] ~ dunif( 0,100 )
}
}
#nBNT priors
for( b in 1:nBetasBNT ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaBNT[ b,yoy,s,1 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
grBetaBNT[ b,yoy,s,2 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
# grBetaBNT[ b,yoy,s,3 ] <- 0
# grBetaBNT[ b,yoy,s,4 ] <- 0
# sigmaBetaBNT[ b,yoy,s,1 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
# sigmaBetaBNT[ b,yoy,s,2 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
# sigmaBetaBNT[ b,yoy,s,3 ] <- 0
# sigmaBetaBNT[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasBNT ) {
for( s in 1:nSeasons ) {
grBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
}
}
##
# for( yoy in 1:2 ) {
# for( s in 1:nSeasons ) {
# grATSOffset[ yoy,s ] ~ dnorm( 0, sd = 30 )
# }
# }
for(ii in 1:nEvalRows) {
lengthExp[ evalRows[ii] + 1 ] <- lengthDATA[ evalRows[ii] ] + gr[ evalRows[ii] ] * sampleInterval[ evalRows[ii] ]
}
############ standardized length for sizeBetas
for( i in 1:(nEvalRows) ){
lengthStd[ evalRows[i] ] <- ( lengthDATA[ evalRows[i] ] - lengthMean ) / lengthSD
}
##
# including this messes up predictions
# for(ii in 1:nFirstObsRows) {
# lengthExp[ firstObsRows[ii] ] <- lengthDATA[ firstObsRows[ii] ]
# }
##
# ## individual random effect on gr
# for(iii in 1:nInd) {
# grIndRE[ iii ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)# )
#
# }
# ##
# sigmaIndRE ~ dunif(0.01,0.5)
# ## individual random effect on gr
for(iii in 1:nMoreThanOneInterval) {
grIndRE[ moreThanOneInterval[iii] ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
}
for(iii in 1:nExactlyOneInterval) {
grIndRE[ exactlyOneInterval[iii] ] <- 0
}
##
sigmaIndRE ~ dunif(0.01,0.5)
})
## ATS
codeSpp[[3]] <- nimbleCode({
##
for( i in 1:nEvalRows ) {
##
mu[ evalRows[i] ] <- lengthDATA[ evalRows[i] ] + ( gr[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
lengthDATA[ evalRows[i] + 1 ] ~ dnorm( mu[ evalRows[i] ],
sd = expectedGRSigma[ evalRows[i] ] * sampleInterval[ evalRows[i] ] )
##
gr[ evalRows[i] ] <-
grInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
# grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
# grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
# # grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd2[evalRows[i]] +
# # grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd2[evalRows[i]] +
# grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
grBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
grBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
grBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
#
grBeta[ 4, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 +
grBeta[ 5, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[ evalRows[i] ]^2 +
# grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[ evalRows[i] ]^2 * flowStd[ evalRows[i] ]^2 +
grBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]]^2 +
grBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]] +
# grBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * lengthStd[evalRows[i]]^2 +
# #
grBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]]^2 +
grBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# #
grBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] +
# grBetaATS[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]]^2 +
grIndRE[ ind[evalRows[i]] ]
##
log( expectedGRSigma[ evalRows[i] ] ) <- #grSigma
sigmaInt[ isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] +
# sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] +
sigmaBeta[ 1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] +
sigmaBeta[ 2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * flowStd[evalRows[i]] +
sigmaBeta[ 3, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]]
# sigmaBetaBNT[1, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] +
# sigmaBetaBNT[2, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * cBKTStd[evalRows[i]] +
# sigmaBetaATS[1, isYOYDATA[evalRows[i]], season[evalRows[i]] ] * cATSStd[evalRows[i]]
# sigmaBeta[ 6, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * tempStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[ 7, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * tempStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[ 8, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * tempStd[evalRows[i]] * ATS01DATA[evalRows[i]] +
# sigmaBeta[ 9, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * tempStd[evalRows[i]] * flowStd[evalRows[i]] +
# sigmaBeta[10, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBKTStd[evalRows[i]] * flowStd[evalRows[i]] * BKT01DATA[evalRows[i]] +
# sigmaBeta[11, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cBNTStd[evalRows[i]] * flowStd[evalRows[i]] * BNT01DATA[evalRows[i]] +
# sigmaBeta[12, isYOYDATA[evalRows[i]], season[evalRows[i]], riverDATA[evalRows[i]] ] * cATSStd[evalRows[i]] * flowStd[evalRows[i]] * ATS01DATA[evalRows[i]]
}
##
for( s in 1:nSeasons ) {
grIntMu[ s ] ~ dnorm(0,sd = 30) #changed from 0.001
grIntSigma[ s ] ~ dunif(0,10)
##
sigmaIntMu[ s ] ~ dnorm(0,sd = 30)
sigmaIntSigma[ s ] ~ dunif(0,10)
##
for( b in 1:nBetas ) { ############# Beta ##############################################################################
grBetaMu[ b,s ] ~ dnorm(0,sd = 30)
grBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( b in 1:nBetasSigma ) { ############# Beta ##############################################################################
sigmaBetaMu[ b,s ] ~ dnorm(0,sd = 30)
sigmaBetaSigma[ b,s ] ~ dunif(0,100)
}
##
for( yoy in 1:2 ) {
for( r in 1:nRivers ) {
grInt[ yoy,s,r ] ~ dnorm( grIntMu[ s ], sd = grIntSigma[ s ] )
sigmaInt[ yoy,s,r ] ~ dnorm( sigmaIntMu[ s ], sd = sigmaIntSigma[ s ] ) #T(0,) #dunif(0,100)
##
for( b in 1:nBetas ) { ############# Beta ##################################################################################
grBeta[ b,yoy,s,r ] ~ dnorm( grBetaMu[ b,s ], sd = grBetaSigma[ b,s ] )
}
for( b in 1:nBetasSigma ) { ############# Beta ##################################################################################
sigmaBeta[ b,yoy,s,r ] ~ dnorm( sigmaBetaMu[ b,s ], sd = sigmaBetaSigma[ b,s ] )
}
}
}
}
# nATS priors
for( b in 1:nBetasATS ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaATS[ b,yoy,s,1 ] ~ dnorm( grBetaATSMu[ b,s ], sd = grBetaATSSigma[ b,s ] )
# sigmaBetaATS[ b,yoy,s ] ~ dnorm( sigmaBetaATSMu[ b,s ], sd = sigmaBetaATSSigma[ b,s ] )
}
}
}
for( b in 1:nBetasATS ) {
for( s in 1:nSeasons ) {
grBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaATSSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaATSMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaATSSigma[ b,s ] ~ dunif( 0,100 )
}
}
#nBNT priors
for( b in 1:nBetasBNT ) {
for( yoy in 1:2 ) {
for( s in 1:nSeasons ) {
grBetaBNT[ b,yoy,s,1 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
#grBetaBNT[ b,yoy,s,2 ] ~ dnorm( grBetaBNTMu[ b,s ], sd = grBetaBNTSigma[ b,s ] )
# grBetaBNT[ b,yoy,s,3 ] <- 0
# grBetaBNT[ b,yoy,s,4 ] <- 0
# sigmaBetaBNT[ b,yoy,s,1 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
#sigmaBetaBNT[ b,yoy,s,2 ] ~ dnorm( sigmaBetaBNTMu[ b,s ], sd = sigmaBetaBNTSigma[ b,s ] )
# sigmaBetaBNT[ b,yoy,s,3 ] <- 0
# sigmaBetaBNT[ b,yoy,s,4 ] <- 0
}
}
}
for( b in 1:nBetasBNT ) {
for( s in 1:nSeasons ) {
grBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
grBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
# sigmaBetaBNTMu[ b,s ] ~ dnorm( 0,sd = 30 )
# sigmaBetaBNTSigma[ b,s ] ~ dunif( 0,100 )
}
}
##
# for( yoy in 1:2 ) {
# for( s in 1:nSeasons ) {
# grATSOffset[ yoy,s ] ~ dnorm( 0, sd = 30 )
# }
# }
for(ii in 1:nEvalRows) {
lengthExp[ evalRows[ii] + 1 ] <- lengthDATA[ evalRows[ii] ] + gr[ evalRows[ii] ] * sampleInterval[ evalRows[ii] ]
}
############ standardized length for sizeBetas
for( i in 1:(nEvalRows) ){
lengthStd[ evalRows[i] ] <- ( lengthDATA[ evalRows[i] ] - lengthMean ) / lengthSD
}
##
# including this messes up predictions
# for(ii in 1:nFirstObsRows) {
# lengthExp[ firstObsRows[ii] ] <- lengthDATA[ firstObsRows[ii] ]
# }
##
## individual random effect on gr
# for(iii in 1:nInd) {
# grIndRE[ iii ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)# )
#
# }
# ##
# sigmaIndRE ~ dunif(0.001,0.5)
for(iii in 1:nMoreThanOneInterval) {
grIndRE[ moreThanOneInterval[iii] ] ~ T(dnorm( 0, sd = sigmaIndRE ), -0.05,0.05)
}
for(iii in 1:nExactlyOneInterval) {
grIndRE[ exactlyOneInterval[iii] ] <- 0
}
##
sigmaIndRE ~ dunif(0.01,0.5)
})
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