Commit 66d74bf6 authored by matbuoro's avatar matbuoro
Browse files

updated for 2016

parent 2db4f330
......@@ -18,8 +18,8 @@ stade <- "adult"
## WORKING DIRECTORY:
work.dir<-paste("/media/ORE/Abundance",site,stade,sep="/")
setwd(work.dir)
# work.dir<-paste("/media/ORE/Abundance",site,stade,sep="/")
# setwd(work.dir)
##-----------------------------DATA ----------------------------------##
......@@ -32,21 +32,29 @@ source(paste('parameters_',stade,'.R',sep="")) # chargement des paramètres
#------------------------INITS----------------------------------##
source(paste('inits/inits_',stade,'.R',sep="")) # création des inits des données
load(paste('inits/inits_',stade,'.Rdata',sep="")) # chargement des inits
if(site == "Bresle" && stade == "adult") {inits <- list(read.bugsdata(paste("inits/init-",site,"-",stade,year,".txt",sep="")))}
if(site == "Nivelle") {inits <- list(read.bugsdata(paste("inits/init-",site,"-",stade,year,".txt",sep="")))}
#if(!file.exists(paste('inits/inits_',stade,year,'.Rdata',sep=""))){
if(!file.exists(paste("inits/init-",site,"-",stade,year,".txt",sep=""))){
source(paste('inits/inits_',stade,'.R',sep="")) # création des inits des données
#load(paste('inits/inits_',stade,year,'.Rdata',sep=""))
}
#load(paste('inits/inits_',stade,'.Rdata',sep="")) # chargement des inits
#if(site == "Bresle" && stade == "adult") {inits <- list(read.bugsdata(paste("inits/init-",site,"-",stade,year,".txt",sep="")))}
#if(site == "Nivelle") {inits <- list(read.bugsdata(paste("inits/init-",site,"-",stade,year,".txt",sep="")))}
inits <- list(read.bugsdata(paste("inits/init-",site,"-",stade,year,".txt",sep="")))
#------------------------MODEL----------------------------------##
model <- paste("model/",stade,"-",site,".R",sep="") # path of the model
model <- paste("model/model_",stade,"-",site,".R",sep="") # path of the model
if(site == "Scorff" && stade == "smolt") {model <- paste("model/",stade,"-",site,"_",year,".R",sep="")} # le modèle Scorrf pour les smolt peut changer tous les ans suivant conditions
model
filename <- file.path(work.dir, model)
#system(paste("cp",model,paste(stade,"-",site,".txt",sep=""),sep=""))
#---------------------------ANALYSIS-----------------------------##
nChains = length(inits) # Number of chains to run.
adaptSteps = 1000 # Number of steps to "tune" the samplers.
nburnin=5000 # Number of steps to "burn-in" the samplers.
nstore=50000 # Total number of steps in chains to save.
nburnin=500 # Number of steps to "burn-in" the samplers.
nstore=1000 # Total number of steps in chains to save.
nthin=1 # Number of steps to "thin" (1=keep every step).
#nPerChain = ceiling( ( numSavedSteps * thinSteps ) / nChains ) # Steps per chain.
......@@ -57,15 +65,23 @@ start.time = Sys.time(); cat("Start of the run\n");
fit <- bugs(
data
,inits
,model.file = model
,model.file = filename
,parameters
,n.chains = nChains, n.iter = nstore + nburnin, n.burnin = nburnin, n.thin = nthin
,DIC=FALSE
,codaPkg = FALSE, clearWD=TRUE
,codaPkg = FALSE, clearWD=FALSE
#,debug=TRUE
,working.directory=work.dir
,working.directory=paste(work.dir,"bugs",sep="/")
)
## cleaning
system("rm bugs/CODA*")
# save last values for inits
#inits <- fit$last.values
#if(site == "Nivelle") {save(inits,file=paste('inits/inits_',stade,year,'.Rdata',sep=""))}
#bugs.inits(inits, n.chains=1,digits=3, inits.files = paste('inits/init-',site,'-',stade,year,'.txt',sep=""))
######### JAGS ##########
## Compile & adapt
......
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list(shape_lambda=5.00000E+00, rate_lambda=1.00000E-02, lambda_tot0=2.89400E+02, a_1.1SW=4.20000E+00, a_1.1SW=8.00000E-02, a_MSW=c(4.00000E-01, 9.05900E-01, 2.51600E+00, 4.55000E-01, 3.03700E-01), eta_1=1.35000E+00, eta_2=5.50000E+00, k_1=8.70000E-01, k_2=1.46000E+00, logit_p_11_1=c(-1.42000E+00, -1.42000E+00, -1.42000E+00, -1.42000E+00, -1.42000E+00, -1.42000E+00, -1.42000E+00, -1.42000E+00), logit_pi_EF=c(-1.68000E+00, -1.68000E+00, -1.68000E+00, -1.68000E+00, -1.68000E+00, -1.68000E+00, -1.68000E+00, -1.68000E+00), mup_11_1=2.10000E-01, mup_11_2=1.80000E-01, mup_21=4.20000E-01, mupi_EF=1.60000E-01, mupi_U=c(8.68900E-01, 8.14600E-01), rho=7.90000E-01, sigmap_11_1=2.10000E-01, sigmap_11_2=9.00000E-02, sigmap_12=c(5.50000E-01, 4.10000E-01, 2.90000E-01, 4.00000E-01), sigmap_21=4.30000E-01, sigmapi_EF=5.20000E-01, sigmapi_U=c(7.34100E-01, 5.64100E-01), alpha_1=c(2.96000E+00, 1.06000E+00, 1.07000E+00, 6.30000E-01, 1.09000E+00, 3.10000E-01, 3.90000E-01, 5.80000E-01, 2.10000E-01, 7.90000E-01, 6.80000E-01, 5.60000E-01, 5.20000E-01, 7.10000E-01, 7.20000E-01, 4.30000E-01, 7.70000E-01, 4.80000E-01, 1.47000E+00, 1.50000E+00, 1.39000E+00, 1.26000E+00, 1.37000E+00, 1.24000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00), alpha_2=c( NA, NA, NA, NA, NA, NA, 8.10000E-01, 9.70000E-01, 1.18000E+00, 2.08000E+00, 1.77000E+00, 1.22000E+00, 1.31000E+00, 1.62000E+00, 1.50000E+00, 1.41000E+00, 1.00000E+00, 9.30000E-01, 2.76000E+00, 2.13000E+00, 2.44000E+00, 1.67000E+00, 2.28000E+00, 2.22000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00), e_21= structure(.Data= c( NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2.00000E+01, 2.30000E+01, 1.00000E+00, 3.00000E+00, 1.90000E+01, 1.10000E+01, 1.00000E+00, 6.00000E+00, 3.10000E+01, 2.80000E+01, 1.00000E+00, 7.00000E+00, 7.60000E+01, 6.70000E+01, 1.00000E+00, 6.00000E+00, 3.90000E+01, 3.20000E+01, 1.00000E+00, 6.00000E+00, 3.20000E+01, 3.00000E+01, 2.00000E+00, 3.00000E+00, 1.90000E+01, 3.80000E+01, 1.00000E+00, 1.20000E+01, 1.00000E+01, 2.20000E+01, 1.00000E+00, 3.00000E+00, 2.70000E+01, 2.60000E+01, 1.00000E+00, 4.00000E+00, 2.60000E+01, 2.60000E+01, 3.00000E+00, 4.00000E+00, 1.90000E+01, 1.40000E+01, NA, 3.00000E+00, 4.20000E+01, 3.00000E+01, 1.00000E+00, 8.00000E+00, 5.50000E+01, 6.00000E+01, 1.00000E+00, 8.00000E+00, 1.00000E+00, 5.00000E+00, 5.00000E+00, 1.00000E+01, 7.00000E+00, 5.00000E+00, NA, 2.00000E+00, 1.10000E+01, 1.10000E+01, NA, 3.00000E+00, 5.00000E+00, 3.00000E+00, 2.00000E+00, 5.00000E+00, 1.00000E+01, 7.00000E+00, 2.00000E+00, 3.00000E+00, 6.00000E+00, 5.00000E+00, NA, 7.00000E+00, 1.50000E+01, 6.00000E+00, NA, 6.00000E+00, 3.00000E+01, 2.50000E+01, 5.00000E+00, 5.00000E+00, 5.00000E+00, 5.00000E+00, 7.00000E+00, 8.00000E+00, 3.00000E+00, 9.00000E+00, 1.00000E+00, 3.00000E+00, 3.00000E+00, 9.00000E+00, 1.00000E+00, 3.00000E+00, 3.00000E+00, 9.00000E+00, 1.00000E+00, 3.00000E+00, 3.00000E+00, 2.00000E+00, 1.00000E+00, 3.00000E+00, 6.00000E+00, 4.00000E+00, 0.00000E+00, 5.00000E+00), .Dim=c(33, 4)), logit_p_11_2=c( NA, NA, NA, NA, NA, NA, NA, NA, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00, -1.98000E+00), logit_p_21=c( NA, NA, NA, NA, NA, NA, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01, 2.80000E-01), logit_pi_U= structure(.Data= c(1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01, 1.77000E+00, 9.80000E-01), .Dim=c(33, 2)), logit_p_n12= structure(.Data= c( NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7.14500E-01, 5.69500E-01, 3.75000E-01, 3.00900E-01, 8.80700E-01, 5.64500E-01, 3.83500E-01, 4.14300E-01, 6.82800E-01, 4.38800E-01, 7.57900E-01, 3.55800E-01, 9.00100E-01, 6.12300E-01, 4.70100E-01, 2.25500E-01, 6.79700E-01, 8.03500E-01, 5.83700E-01, 5.93600E-01, 6.25600E-01, 7.10600E-01, 6.62000E-01, 4.64900E-01, 6.67400E-01, 7.37100E-01, 6.38600E-01, 5.84000E-01, 8.12100E-01, 7.68100E-01, 6.27600E-01, 4.32600E-01, 6.75300E-01, 6.20000E-01, 5.34900E-01, 3.69400E-01, 8.18400E-01, 6.87500E-01, 4.17100E-01, 5.99000E-01, 5.36100E-01, 6.36200E-01, 4.27700E-01, 4.70300E-01, 6.01100E-01, 6.91900E-01, 7.27400E-01, 4.54800E-01, 4.88600E-01, 4.17400E-01, 3.24600E-01, 3.72300E-01, 7.50400E-01, 6.15400E-01, 5.45800E-01, 4.55200E-01, 5.78100E-01, 5.54400E-01, 6.49700E-01, 4.26600E-01, 7.84700E-01, 6.11400E-01, 6.46700E-01, 4.57700E-01, 5.89100E-01, 4.39400E-01, 3.23100E-01, 5.60600E-01, 7.60500E-01, 6.75400E-01, 5.46800E-01, 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3.00000E+00, 1.20000E+01, 9.00000E+00, 0.00000E+00, 3.00000E+00, 2.00000E+00, 1.40000E+01, 0.00000E+00, 3.00000E+00, 3.50000E+01, 3.20000E+01, 0.00000E+00, 4.00000E+00, 1.00000E+00, 2.00000E+00, 1.00000E+00, 7.00000E+00, 6.00000E+00, 7.00000E+00, 0.00000E+00, 2.00000E+00, 5.00000E+00, 7.00000E+00, 0.00000E+00, 1.00000E+00, 3.00000E+00, 2.00000E+00, 0.00000E+00, 3.00000E+00, 4.00000E+00, 4.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00), .Dim=c(33, 4)), p_1.1SW=c(1.00000E+00, 1.00000E+00, 1.00000E+00, 1.00000E+00, 9.56700E-01, 1.00000E+00, 1.00000E+00, 1.00000E+00, 8.39700E-01, 9.36300E-01, 1.00000E+00, 1.00000E+00, 9.99700E-01, 9.99600E-01, 1.00000E+00, 9.98100E-01, 9.48700E-01, 1.00000E+00, 1.00000E+00, 9.93200E-01, 7.13100E-01, 1.00000E+00, 6.24200E-01, 9.88600E-01, 1.00000E+00, 9.49600E-01, 1.00000E+00, 1.00000E+00, 1.00000E+00, 9.80000E-01, 9.50000E-01, 9.50000E-01, 8.00000E-01), no_ech_1.1SW=c(1.57000E+02, 1.40000E+01, 7.80000E+01, 6.30000E+01, 6.30000E+01, 4.90000E+01, 8.80000E+01, 3.10000E+01, 3.60000E+01, 3.11000E+02, 2.21000E+02, 4.50000E+01, 3.30000E+01, 2.40000E+01, 3.40000E+01, 4.30000E+01, 2.60000E+01, 3.50000E+01, 1.54000E+02, 7.00000E+00, 1.30000E+01, 1.80000E+01, 7.00000E+00, 1.30000E+01, 8.00000E+00, 1.30000E+01, 5.00000E+00, 3.00000E+00, 2.00000E+00, 5.00000E+00, 5.00000E+00, 2.00000E+00, 5.00000E+00), no_ech_MSW= structure(.Data= c(2.00000E+00, 4.00000E+00, 2.00000E+00, 2.00000E+00, NA, 0.00000E+00, 2.00000E+00, 7.00000E+00, 1.00000E+00, NA, 2.00000E+00, 0.00000E+00, 7.00000E+00, 1.00000E+00, NA, 0.00000E+00, 1.00000E+00, 4.00000E+00, 5.00000E+00, NA, 0.00000E+00, 6.00000E+00, 8.00000E+00, 5.00000E+00, NA, 2.00000E+00, 9.00000E+00, 1.30000E+01, 0.00000E+00, NA, 0.00000E+00, 1.00000E+00, 6.00000E+00, 1.00000E+00, NA, 5.00000E+00, 0.00000E+00, 1.80000E+01, 1.00000E+00, NA, 0.00000E+00, 0.00000E+00, 1.20000E+01, 0.00000E+00, NA, 1.60000E+01, 1.30000E+01, 9.00000E+00, 4.00000E+00, NA, 1.00000E+00, 1.20000E+01, 1.50000E+01, 0.00000E+00, NA, 3.00000E+00, 0.00000E+00, 1.90000E+01, 3.00000E+00, NA, 0.00000E+00, 3.00000E+00, 2.00000E+00, 9.00000E+00, NA, 1.00000E+00, 2.00000E+00, 1.00000E+00, 0.00000E+00, NA, 0.00000E+00, 5.00000E+00, 1.00000E+00, 0.00000E+00, NA, 5.00000E+00, 8.00000E+00, 9.00000E+00, 3.00000E+00, NA, 0.00000E+00, 4.00000E+00, 2.00000E+00, 1.00000E+00, NA, 8.00000E+00, 0.00000E+00, 1.00000E+01, 1.00000E+00, NA, 0.00000E+00, 5.00000E+00, 7.00000E+00, 0.00000E+00, NA, 0.00000E+00, 0.00000E+00, 1.10000E+01, 0.00000E+00, NA, 1.00000E+00, 0.00000E+00, 4.00000E+00, 0.00000E+00, NA, 3.00000E+00, 0.00000E+00, 1.00000E+00, 1.00000E+00, NA, 4.00000E+00, 0.00000E+00, 5.00000E+00, 2.00000E+00, NA, 0.00000E+00, 3.00000E+00, 3.00000E+00, 2.00000E+00, NA, 0.00000E+00, 3.00000E+00, 4.00000E+00, 0.00000E+00, NA, 1.00000E+00, 0.00000E+00, 3.00000E+00, 0.00000E+00, NA, 2.00000E+00, 0.00000E+00, 2.00000E+00, 0.00000E+00, NA, 0.00000E+00, 0.00000E+00, 2.00000E+00, 5.00000E+00, NA, 2.00000E+00, 0.00000E+00, 2.00000E+00, 0.00000E+00, NA, 4.00000E+00, 0.00000E+00, 5.00000E+00, 2.00000E+00, NA, 8.00000E+00, 0.00000E+00, 1.00000E+01, 1.00000E+00, NA, 3.00000E+00, 1.00000E+00, 0.00000E+00, 0.00000E+00, NA, 0.00000E+00, 1.00000E+00, 5.00000E+00, 0.00000E+00, NA), .Dim=c(33, 5)))
OpenBUGS version 3.2.3 rev 1012
model is syntactically correct
data loaded (variables not in the model: Dm_12, Dum_12, Am_12, Aum_12)
model compiled
initial values loaded but chain contain uninitialized variables
initial values generated, model initialized
500 updates took 3 s
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inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
inference can not be made when sampler is in adaptive phase
1000 updates took 8 s
CODA files written
no monitors set
modelCheck('/home/basp-meco88/Documents/RESEARCH/PROJECTS/ORE/Abundance/Nivelle/adult/bugs/model_adult-Nivelle.R.txt')
modelData('/home/basp-meco88/Documents/RESEARCH/PROJECTS/ORE/Abundance/Nivelle/adult/bugs/data.txt')
modelCompile(1)
modelSetRN(1)
modelInits('/home/basp-meco88/Documents/RESEARCH/PROJECTS/ORE/Abundance/Nivelle/adult/bugs/inits1.txt',1)
modelGenInits()
modelUpdate(500,1,500)
samplesSet(mup_11_1)
samplesSet(sigmap_11_1)
samplesSet(mup_11_2)
samplesSet(sigmap_11_2)
samplesSet(mupi_U)
samplesSet(sigmapi_U)
samplesSet(mupi_EF)
samplesSet(sigmapi_EF)
samplesSet(mup_n12)
samplesSet(sigmap_12)
samplesSet(mup_21)
samplesSet(sigmap_21)
samplesSet(p_11_1)
samplesSet(p_11_2)
samplesSet(pi_U)
samplesSet(eps_U)
samplesSet(pi_U_eff)
samplesSet(pi_EF)
samplesSet(p_n12)
samplesSet(eps_Ol)
samplesSet(p_21)
samplesSet(test_p_12)
samplesSet(k_1)
samplesSet(k_2)
samplesSet(RPF)
samplesSet(alpha_1)
samplesSet(eta_1)
samplesSet(alpha_2)
samplesSet(eta_2)
samplesSet(rho)
samplesSet(lambda_tot)
samplesSet(Plambda)
samplesSet(shape_lambda)
samplesSet(rate_lambda)
samplesSet(lambda_tot0)
samplesSet(Plambda0)
samplesSet(s)
samplesSet(n_tot)
samplesSet(n_1SW)
samplesSet(n_MSW)
samplesSet(n_11)
samplesSet(e_11)
samplesSet(e_11_tot)
samplesSet(e_12)
samplesSet(e_12_tot)
samplesSet(e_21)
samplesSet(e_21_tot)
samplesSet(e_22)
samplesSet(e_22_tot)
samplesSet(e_1SW)
samplesSet(e_MSW)
samplesSet(e_1SW_F)
samplesSet(e_MSW_F)
samplesSet(eggs_11)
samplesSet(eggs_12)
samplesSet(eggs_21)
samplesSet(eggs_22)
samplesSet(eggs_tot)
samplesSet(a_1.1SW)
samplesSet(a_2.1SW)
samplesSet(a_MSW)
samplesSet(c_1SW)
samplesSet(c_2SW)
samplesSet(c_3SW)
samplesSet(c_tot)
samplesSet(P_1SW)
samplesSet(P_MSW)
summarySet(mup_11_1)
summarySet(sigmap_11_1)
summarySet(mup_11_2)
summarySet(sigmap_11_2)
summarySet(mupi_U)
summarySet(sigmapi_U)
summarySet(mupi_EF)
summarySet(sigmapi_EF)
summarySet(mup_n12)
summarySet(sigmap_12)
summarySet(mup_21)
summarySet(sigmap_21)
summarySet(p_11_1)
summarySet(p_11_2)
summarySet(pi_U)
summarySet(eps_U)
summarySet(pi_U_eff)
summarySet(pi_EF)
summarySet(p_n12)
summarySet(eps_Ol)
summarySet(p_21)
summarySet(test_p_12)
summarySet(k_1)
summarySet(k_2)
summarySet(RPF)
summarySet(alpha_1)
summarySet(eta_1)
summarySet(alpha_2)
summarySet(eta_2)
summarySet(rho)
summarySet(lambda_tot)
summarySet(Plambda)
summarySet(shape_lambda)
summarySet(rate_lambda)
summarySet(lambda_tot0)
summarySet(Plambda0)
summarySet(s)
summarySet(n_tot)
summarySet(n_1SW)
summarySet(n_MSW)
summarySet(n_11)
summarySet(e_11)
summarySet(e_11_tot)
summarySet(e_12)
summarySet(e_12_tot)
summarySet(e_21)
summarySet(e_21_tot)
summarySet(e_22)
summarySet(e_22_tot)
summarySet(e_1SW)
summarySet(e_MSW)
summarySet(e_1SW_F)
summarySet(e_MSW_F)
summarySet(eggs_11)
summarySet(eggs_12)
summarySet(eggs_21)
summarySet(eggs_22)
summarySet(eggs_tot)
summarySet(a_1.1SW)
summarySet(a_2.1SW)
summarySet(a_MSW)
summarySet(c_1SW)
summarySet(c_2SW)
summarySet(c_3SW)
summarySet(c_tot)
summarySet(P_1SW)
summarySet(P_MSW)
modelUpdate(1000,1,1000)
samplesCoda('*', '/home/basp-meco88/Documents/RESEARCH/PROJECTS/ORE/Abundance/Nivelle/adult/bugs//')
summaryStats('*')
modelQuit('y')
list(shape_lambda=5.000E+00, rate_lambda=1.000E-02, lambda_tot0=2.894E+02, a_1.1SW=4.200E+00, a_1.1SW=8.000E-02, a_MSW=c(4.000E-01, 9.059E-01, 2.516E+00, 4.550E-01, 3.037E-01), eta_1=1.350E+00, eta_2=5.500E+00, k_1=8.700E-01, k_2=1.460E+00, logit_p_11_1=c(-1.420E+00, -1.420E+00, -1.420E+00, -1.420E+00, -1.420E+00, -1.420E+00, -1.420E+00, -1.420E+00), logit_pi_EF=c(-1.680E+00, -1.680E+00, -1.680E+00, -1.680E+00, -1.680E+00, -1.680E+00, -1.680E+00, -1.680E+00), mup_11_1=2.100E-01, mup_11_2=1.800E-01, mup_21=4.200E-01, mupi_EF=1.600E-01, mupi_U=c(8.689E-01, 8.146E-01), rho=7.900E-01, sigmap_11_1=2.100E-01, sigmap_11_2=9.000E-02, sigmap_12=c(5.500E-01, 4.100E-01, 2.900E-01, 4.000E-01), sigmap_21=4.300E-01, sigmapi_EF=5.200E-01, sigmapi_U=c(7.341E-01, 5.641E-01), alpha_1=c(2.960E+00, 1.060E+00, 1.070E+00, 6.300E-01, 1.090E+00, 3.100E-01, 3.900E-01, 5.800E-01, 2.100E-01, 7.900E-01, 6.800E-01, 5.600E-01, 5.200E-01, 7.100E-01, 7.200E-01, 4.300E-01, 7.700E-01, 4.800E-01, 1.470E+00, 1.500E+00, 1.390E+00, 1.260E+00, 1.370E+00, 1.240E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00), alpha_2=c( NA, NA, NA, NA, NA, NA, 8.100E-01, 9.700E-01, 1.180E+00, 2.080E+00, 1.770E+00, 1.220E+00, 1.310E+00, 1.620E+00, 1.500E+00, 1.410E+00, 1.000E+00, 9.300E-01, 2.760E+00, 2.130E+00, 2.440E+00, 1.670E+00, 2.280E+00, 2.220E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00), e_21= structure(.Data= c( NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2.000E+01, 2.300E+01, 1.000E+00, 3.000E+00, 1.900E+01, 1.100E+01, 1.000E+00, 6.000E+00, 3.100E+01, 2.800E+01, 1.000E+00, 7.000E+00, 7.600E+01, 6.700E+01, 1.000E+00, 6.000E+00, 3.900E+01, 3.200E+01, 1.000E+00, 6.000E+00, 3.200E+01, 3.000E+01, 2.000E+00, 3.000E+00, 1.900E+01, 3.800E+01, 1.000E+00, 1.200E+01, 1.000E+01, 2.200E+01, 1.000E+00, 3.000E+00, 2.700E+01, 2.600E+01, 1.000E+00, 4.000E+00, 2.600E+01, 2.600E+01, 3.000E+00, 4.000E+00, 1.900E+01, 1.400E+01, NA, 3.000E+00, 4.200E+01, 3.000E+01, 1.000E+00, 8.000E+00, 5.500E+01, 6.000E+01, 1.000E+00, 8.000E+00, 1.000E+00, 5.000E+00, 5.000E+00, 1.000E+01, 7.000E+00, 5.000E+00, NA, 2.000E+00, 1.100E+01, 1.100E+01, NA, 3.000E+00, 5.000E+00, 3.000E+00, 2.000E+00, 5.000E+00, 1.000E+01, 7.000E+00, 2.000E+00, 3.000E+00, 6.000E+00, 5.000E+00, NA, 7.000E+00, 1.500E+01, 6.000E+00, NA, 6.000E+00, 3.000E+01, 2.500E+01, 5.000E+00, 5.000E+00, 5.000E+00, 5.000E+00, 7.000E+00, 8.000E+00, 3.000E+00, 9.000E+00, 1.000E+00, 3.000E+00, 3.000E+00, 9.000E+00, 1.000E+00, 3.000E+00, 3.000E+00, 9.000E+00, 1.000E+00, 3.000E+00, 3.000E+00, 2.000E+00, 1.000E+00, 3.000E+00, 6.000E+00, 4.000E+00, 0.000E+00, 5.000E+00), .Dim=c(33, 4)), logit_p_11_2=c( NA, NA, NA, NA, NA, NA, NA, NA, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00, -1.980E+00), logit_p_21=c( NA, NA, NA, NA, NA, NA, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01, 2.800E-01), logit_pi_U= structure(.Data= c(1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01, 1.770E+00, 9.800E-01), .Dim=c(33, 2)), logit_p_n12= structure(.Data= c( NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7.145E-01, 5.695E-01, 3.750E-01, 3.009E-01, 8.807E-01, 5.645E-01, 3.835E-01, 4.143E-01, 6.828E-01, 4.388E-01, 7.579E-01, 3.558E-01, 9.001E-01, 6.123E-01, 4.701E-01, 2.255E-01, 6.797E-01, 8.035E-01, 5.837E-01, 5.936E-01, 6.256E-01, 7.106E-01, 6.620E-01, 4.649E-01, 6.674E-01, 7.371E-01, 6.386E-01, 5.840E-01, 8.121E-01, 7.681E-01, 6.276E-01, 4.326E-01, 6.753E-01, 6.200E-01, 5.349E-01, 3.694E-01, 8.184E-01, 6.875E-01, 4.171E-01, 5.990E-01, 5.361E-01, 6.362E-01, 4.277E-01, 4.703E-01, 6.011E-01, 6.919E-01, 7.274E-01, 4.548E-01, 4.886E-01, 4.174E-01, 3.246E-01, 3.723E-01, 7.504E-01, 6.154E-01, 5.458E-01, 4.552E-01, 5.781E-01, 5.544E-01, 6.497E-01, 4.266E-01, 7.847E-01, 6.114E-01, 6.467E-01, 4.577E-01, 5.891E-01, 4.394E-01, 3.231E-01, 5.606E-01, 7.605E-01, 6.754E-01, 5.468E-01, 5.673E-01, 7.693E-01, 6.373E-01, 7.643E-01, 5.382E-01, 7.233E-01, 5.082E-01, 8.754E-01, 4.834E-01, 6.227E-01, 6.204E-01, 6.583E-01, 3.513E-01, 5.049E-01, 5.467E-01, 4.616E-01, 6.162E-01, 5.049E-01, 5.467E-01, 4.616E-01, 6.162E-01, 5.049E-01, 5.467E-01, 4.616E-01, 6.162E-01, 5.049E-01, 5.467E-01, 4.616E-01, 6.162E-01), .Dim=c(33, 4)), n= structure(.Data= c(7.100E+01, 1.010E+02, 8.000E+00, 1.500E+01, 4.200E+01, 3.500E+01, 9.000E+00, 3.800E+01, 1.540E+02, 1.580E+02, 1.100E+01, 3.000E+01, 7.800E+01, 1.340E+02, 1.000E+01, 4.100E+01, 8.400E+01, 5.800E+01, 4.000E+00, 4.100E+01, 1.040E+02, 1.040E+02, 1.800E+01, 4.900E+01, 1.410E+02, 1.500E+02, 1.100E+01, 2.900E+01, 6.800E+01, 7.500E+01, 1.400E+01, 4.900E+01, 1.040E+02, 1.140E+02, 1.000E+01, 4.600E+01, 2.650E+02, 3.240E+02, 8.000E+00, 5.500E+01, 1.810E+02, 2.170E+02, 6.000E+00, 5.000E+01, 9.100E+01, 1.040E+02, 1.700E+01, 4.300E+01, 7.800E+01, 1.100E+02, 7.000E+00, 5.200E+01, 4.500E+01, 8.000E+01, 3.000E+00, 1.200E+01, 9.000E+01, 8.200E+01, 5.000E+00, 1.400E+01, 8.100E+01, 7.800E+01, 1.900E+01, 2.800E+01, 7.400E+01, 5.900E+01, 7.000E+00, 2.400E+01, 9.500E+01, 8.900E+01, 5.000E+00, 3.200E+01, 2.120E+02, 2.000E+02, 5.000E+00, 3.600E+01, 1.300E+01, 1.800E+01, 1.300E+01, 4.900E+01, 4.300E+01, 4.600E+01, 4.000E+00, 1.700E+01, 3.900E+01, 4.800E+01, 2.000E+00, 1.300E+01, 2.500E+01, 2.100E+01, 7.000E+00, 2.700E+01, 3.400E+01, 3.100E+01, 6.000E+00, 1.500E+01, 2.500E+01, 3.000E+01, 5.000E+00, 2.500E+01, 3.500E+01, 2.000E+01, 2.000E+00, 2.000E+01, 7.000E+01, 6.000E+01, 1.000E+01, 1.500E+01, 1.500E+01, 2.500E+01, 1.500E+01, 3.000E+01, 7.500E+01, 1.670E+02, 9.600E+01, 8.300E+01, 9.500E+01, 1.870E+02, 1.030E+02, 9.300E+01, 1.040E+02, 1.140E+02, 1.000E+01, 4.600E+01, 2.500E+01, 1.500E+01, 1.000E+01, 2.500E+01, 3.200E+01, 9.000E+00, 4.000E+00, 2.400E+01), .Dim=c(33, 4)), n_11= structure(.Data= c(9.000E+00, 1.800E+01, 0.000E+00, 2.000E+00, 6.000E+00, 5.000E+00, 1.000E+00, 6.000E+00, 2.800E+01, 2.900E+01, 1.000E+00, 5.000E+00, 1.100E+01, 1.900E+01, 1.000E+00, 5.000E+00, 9.000E+00, 7.000E+00, 0.000E+00, 4.000E+00, 2.100E+01, 2.200E+01, 2.000E+00, 8.000E+00, 1.800E+01, 2.600E+01, 1.000E+00, 4.000E+00, 1.200E+01, 1.400E+01, 2.000E+00, 6.000E+00, 1.600E+01, 1.800E+01, 1.000E+00, 7.000E+00, 3.400E+01, 4.800E+01, 0.000E+00, 6.000E+00, 2.500E+01, 3.100E+01, 0.000E+00, 6.000E+00, 1.300E+01, 1.600E+01, 1.000E+00, 6.000E+00, 1.100E+01, 1.600E+01, 1.000E+00, 6.000E+00, 6.000E+00, 1.100E+01, 0.000E+00, 1.000E+00, 1.300E+01, 1.200E+01, 0.000E+00, 1.000E+00, 1.200E+01, 1.100E+01, 1.000E+00, 3.000E+00, 1.200E+01, 9.000E+00, 0.000E+00, 3.000E+00, 2.000E+00, 1.400E+01, 0.000E+00, 3.000E+00, 3.500E+01, 3.200E+01, 0.000E+00, 4.000E+00, 1.000E+00, 2.000E+00, 1.000E+00, 7.000E+00, 6.000E+00, 7.000E+00, 0.000E+00, 2.000E+00, 5.000E+00, 7.000E+00, 0.000E+00, 1.000E+00, 3.000E+00, 2.000E+00, 0.000E+00, 3.000E+00, 4.000E+00, 4.000E+00, 0.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00), .Dim=c(33, 4)), p_1.1SW=c(1.000E+00, 1.000E+00, 1.000E+00, 1.000E+00, 9.567E-01, 1.000E+00, 1.000E+00, 1.000E+00, 8.397E-01, 9.363E-01, 1.000E+00, 1.000E+00, 9.997E-01, 9.996E-01, 1.000E+00, 9.981E-01, 9.487E-01, 1.000E+00, 1.000E+00, 9.932E-01, 7.131E-01, 1.000E+00, 6.242E-01, 9.886E-01, 1.000E+00, 9.496E-01, 1.000E+00, 1.000E+00, 1.000E+00, 9.800E-01, 9.500E-01, 9.500E-01, 8.000E-01), no_ech_1.1SW=c(1.570E+02, 1.400E+01, 7.800E+01, 6.300E+01, 6.300E+01, 4.900E+01, 8.800E+01, 3.100E+01, 3.600E+01, 3.110E+02, 2.210E+02, 4.500E+01, 3.300E+01, 2.400E+01, 3.400E+01, 4.300E+01, 2.600E+01, 3.500E+01, 1.540E+02, 7.000E+00, 1.300E+01, 1.800E+01, 7.000E+00, 1.300E+01, 8.000E+00, 1.300E+01, 5.000E+00, 3.000E+00, 2.000E+00, 5.000E+00, 5.000E+00, 2.000E+00, 5.000E+00), no_ech_MSW= structure(.Data= c(2.000E+00, 4.000E+00, 2.000E+00, 2.000E+00, NA, 0.000E+00, 2.000E+00, 7.000E+00, 1.000E+00, NA, 2.000E+00, 0.000E+00, 7.000E+00, 1.000E+00, NA, 0.000E+00, 1.000E+00, 4.000E+00, 5.000E+00, NA, 0.000E+00, 6.000E+00, 8.000E+00, 5.000E+00, NA, 2.000E+00, 9.000E+00, 1.300E+01, 0.000E+00, NA, 0.000E+00, 1.000E+00, 6.000E+00, 1.000E+00, NA, 5.000E+00, 0.000E+00, 1.800E+01, 1.000E+00, NA, 0.000E+00, 0.000E+00, 1.200E+01, 0.000E+00, NA, 1.600E+01, 1.300E+01, 9.000E+00, 4.000E+00, NA, 1.000E+00, 1.200E+01, 1.500E+01, 0.000E+00, NA, 3.000E+00, 0.000E+00, 1.900E+01, 3.000E+00, NA, 0.000E+00, 3.000E+00, 2.000E+00, 9.000E+00, NA, 1.000E+00, 2.000E+00, 1.000E+00, 0.000E+00, NA, 0.000E+00, 5.000E+00, 1.000E+00, 0.000E+00, NA, 5.000E+00, 8.000E+00, 9.000E+00, 3.000E+00, NA, 0.000E+00, 4.000E+00, 2.000E+00, 1.000E+00, NA, 8.000E+00, 0.000E+00, 1.000E+01, 1.000E+00, NA, 0.000E+00, 5.000E+00, 7.000E+00, 0.000E+00, NA, 0.000E+00, 0.000E+00, 1.100E+01, 0.000E+00, NA, 1.000E+00, 0.000E+00, 4.000E+00, 0.000E+00, NA, 3.000E+00, 0.000E+00, 1.000E+00, 1.000E+00, NA, 4.000E+00, 0.000E+00, 5.000E+00, 2.000E+00, NA, 0.000E+00, 3.000E+00, 3.000E+00, 2.000E+00, NA, 0.000E+00, 3.000E+00, 4.000E+00, 0.000E+00, NA, 1.000E+00, 0.000E+00, 3.000E+00, 0.000E+00, NA, 2.000E+00, 0.000E+00, 2.000E+00, 0.000E+00, NA, 0.000E+00, 0.000E+00, 2.000E+00, 5.000E+00, NA, 2.000E+00, 0.000E+00, 2.000E+00, 0.000E+00, NA, 4.000E+00, 0.000E+00, 5.000E+00, 2.000E+00, NA, 8.000E+00, 0.000E+00, 1.000E+01, 1.000E+00, NA, 3.000E+00, 1.000E+00, 0.000E+00, 0.000E+00, NA, 0.000E+00, 1.000E+00, 5.000E+00, 0.000E+00, NA), .Dim=c(33, 5)))
......@@ -12,13 +12,10 @@
load(paste('data/data_',stade,"_",year,'.Rdata',sep=""))
#------------------------INITS----------------------------------##
# inits<-function(){
# list(
# beta=rnorm(1,0,1)
# )}
inits0 <- read.bugsdata(paste("inits/init-",site,"-",stade,as.numeric(year)-1,".txt",sep=""))
#save(inits0,file=paste('inits/inits_',stade,as.numeric(year)-1,'.Rdata',sep=""))
#load(paste('inits/inits_',stade,as.numeric(year)-1,'.Rdata',sep=""))
#inits1 <- read.bugsdata(paste("inits/init-",site,"-",stade,year,".txt",sep=""))
#inits<-list(inits1)#inits2,inits3)
###################################################
# NO UPDATE
......@@ -58,266 +55,304 @@ inits_fix <- list(
# TO UPDATE
###################################################
inits_updated <- list(
#inits_updated <- list(
# Les p_MSW ne sont pas initialis?es, ? dessein
# initialisation par BUGS pours assurer une somme ?gale ? 1
## METTRE A JOUR
alpha_1 = c(
2.96,1.06,1.07,0.63,1.09,
0.31,0.39,0.58,0.21,0.79,
0.68,0.56,0.52,0.71,0.72,
0.43,0.77,0.48,1.47,1.5,
1.39,1.26,1.37,1.24,1.0,
1.0,1.0,1.0, 1.0,1,
1,1),
# alpha_1 = c(
# 2.96,1.06,1.07,0.63,1.09,
# 0.31,0.39,0.58,0.21,0.79,
# 0.68,0.56,0.52,0.71,0.72,
# 0.43,0.77,0.48,1.47,1.5,
# 1.39,1.26,1.37,1.24,1.0,
# 1.0,1.0,1.0, 1.0,1,
# 1,1),
alpha_1 <- c(inits0$alpha_1, 1) # ajouter 1
## METTRE A JOUR
alpha_2 = c(
NA, NA, NA, NA, NA,
NA,0.81,0.97,1.18,2.08,
1.77,1.22,1.31,1.62,1.5,
1.41,1.0,0.93,2.76,2.13,
2.44,1.67,2.28,2.22,1.0,
1.0,1.0,1.0,1.0,1,
1,1),
# alpha_2 = c(
# NA, NA, NA, NA, NA,
# NA,0.81,0.97,1.18,2.08,
# 1.77,1.22,1.31,1.62,1.5,
# 1.41,1.0,0.93,2.76,2.13,
# 2.44,1.67,2.28,2.22,1.0,
# 1.0,1.0,1.0,1.0,1,
# 1,1),
alpha_2 <- c(inits0$alpha_2, 1) # ajouter 1
## METTRE A JOUR /!\ TAILLE MATRICE
e_21 = structure(.Data = c(
NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA,
NA, NA, NA, NA,20.0,
23.0,1.0,3.0,19.0,11.0,
1.0,6.0,31.0,28.0,1.0,
7.0,76.0,67.0,1.0,6.0,
39.0,32.0,1.0,6.0,32.0,
30.0,2.0,3.0,19.0,38.0,
1.0,12.0,10.0,22.0,1.0,
3.0,27.0,26.0,1.0,4.0,
26.0,26.0,3.0,4.0,19.0,
14.0,NA,3.0,42.0,30.0,
1.0,8.0,55.0,60.0,1.0,
8.0,1.0,5.0,5.0,10.0,
7.0,5.0, NA,2.0,11.0,
11.0, NA,3.0,5.0,3.0,
2.0,5.0,10.0,7.0,2.0,
3.0,6.0,5.0, NA,7.0,
15.0,6.0, NA,6.0,30.0,
25.0,5.0,5.0,5.0,5.0,
7.0,8.0,
3.0,9.0,1.0,3.0,
3.0,9.0,1.0,3.0,
3.0,9.0,1.0,3.0,
3.0,2.0,1.0,3.0),
.Dim = c(32,4)),
# e_21 = structure(.Data = c(
# NA, NA, NA, NA, NA,
# NA, NA, NA, NA, NA,
# NA, NA, NA, NA, NA,
# NA, NA, NA, NA, NA,
# NA, NA, NA, NA,20.0,
# 23.0,1.0,3.0,19.0,11.0,
# 1.0,6.0,31.0,28.0,1.0,
# 7.0,76.0,67.0,1.0,6.0,
# 39.0,32.0,1.0,6.0,32.0,
# 30.0,2.0,3.0,19.0,38.0,
# 1.0,12.0,10.0,22.0,1.0,
# 3.0,27.0,26.0,1.0,4.0,
# 26.0,26.0,3.0,4.0,19.0,
# 14.0,NA,3.0,42.0,30.0,
# 1.0,8.0,55.0,60.0,1.0,
# 8.0,1.0,5.0,5.0,10.0,
# 7.0,5.0, NA,2.0,11.0,
# 11.0, NA,3.0,5.0,3.0,
# 2.0,5.0,10.0,7.0,2.0,
# 3.0,6.0,5.0, NA,7.0,
# 15.0,6.0, NA,6.0,30.0,
# 25.0,5.0,5.0,5.0,5.0,
# 7.0,8.0,
# 3.0,9.0,1.0,3.0,
# 3.0,9.0,1.0,3.0,
# 3.0,9.0,1.0,3.0,
# 3.0,2.0,1.0,3.0),
# .Dim = c(32,4)),
e_2.tmp = ((data$Cm_O[data$Y, ] + data$Cum_O[data$Y, ])/ tail(data$eff_Ol,n=1)) + data$NB[data$Y, ]
e_21.tmp = ceiling(e_2.tmp / 2)
e_21 = rbind(inits0$e_21, e_21.tmp)
## METTRE A JOUR
logit_p_11_2 = c(
NA, NA, NA, NA, NA,
NA, NA, NA,-1.98,-1.98,
-1.98,-1.98,-1.98,-1.98,-1.98,
-1.98,-1.98,-1.98,-1.98,-1.98,
-1.98,-1.98,-1.98,-1.98,-1.98,
-1.98,-1.98,-1.98,-1.98,-1.98,
-1.98,-1.98),
# logit_p_11_2 = c(
# NA, NA, NA, NA, NA,
# NA, NA, NA,-1.98,-1.98,
# -1.98,-1.98,-1.98,-1.98,-1.98,
# -1.98,-1.98,-1.98,-1.98,-1.98,
# -1.98,-1.98,-1.98,-1.98,-1.98,
# -1.98,-1.98,-1.98,-1.98,-1.98,
# -1.98,-1.98),
logit_p_11_2 <- c(inits0$logit_p_11_2, -1.98) # ajouter 1
## METTRE A JOUR
logit_p_21 = c(
NA, NA, NA, NA, NA,
NA,0.28,0.28,0.28,0.28,
0.28,0.28,0.28,0.28,0.28,
0.28,0.28,0.28,0.28,0.28,
0.28,0.28,0.28,0.28,0.28,
0.28,0.28,0.28,0.28,0.28,
0.28,0.28),
# logit_p_21 = c(
# NA, NA, NA, NA, NA,
# NA,0.28,0.28,0.28,0.28,
# 0.28,0.28,0.28,0.28,0.28,
# 0.28,0.28,0.28,0.28,0.28,
# 0.28,0.28,0.28,0.28,0.28,
# 0.28,0.28,0.28,0.28,0.28,
# 0.28,0.28),
logit_p_21 <- c(inits0$logit_p_21, 0.28) # ajouter 1
## METTRE A JOUR /!\ TAILLE MATRICE
logit_pi_U = structure(.Data = c(
1.77,0.98,1.77,0.98,1.77,
0.98,1.77,0.98,1.77,0.98,
1.77,0.98,1.77,0.98,1.77,
0.98,1.77,0.98,1.77,0.98,
1.77,0.98,1.77,0.98,1.77,
0.98,1.77,0.98,1.77,0.98,
1.77,0.98,1.77,0.98,1.77,
0.98,1.77,0.98,1.77,0.98,
1.77,0.98,1.77,0.98,1.77,
0.98,1.77,0.98,1.77,0.98,
1.77,0.98,1.77,0.98,1.77,
0.98,1.77,0.98,1.77,0.98,
0.98,1.77,0.98,1.77),
.Dim = c(32,2)),
# logit_pi_U = structure(.Data = c(
# 1.77,0.98,1.77,0.98,1.77,
# 0.98,1.77,0.98,1.77,0.98,
# 1.77,0.98,1.77,0.98,1.77,
# 0.98,1.77,0.98,1.77,0.98,
# 1.77,0.98,1.77,0.98,1.77,
# 0.98,1.77,0.98,1.77,0.98,
# 1.77,0.98,1.77,0.98,1.77,
# 0.98,1.77,0.98,1.77,0.98,
# 1.77,0.98,1.77,0.98,1.77,
# 0.98,1.77,0.98,1.77,0.98,
# 1.77,0.98,1.77,0.98,1.77,
# 0.98,1.77,0.98,1.77,0.98,
# 0.98,1.77,0.98,1.77),
# .Dim = c(32,2)),
logit_pi_U <- rbind(inits0$logit_pi_U, c(1.77, 0.98))
## METTRE A JOUR /!\ TAILLE MATRICE
logit_p_n12 = structure(.Data = c(
NA , NA , NA , NA ,
NA , NA , NA , NA ,
NA , NA , NA , NA ,
NA , NA , NA , NA ,
NA , NA , NA , NA ,
NA , NA , NA , NA ,
NA , NA , NA , NA ,
NA , NA , NA , NA ,
0.7145 , 0.5695 , 0.375 , 0.3009 ,
0.8807 , 0.5645 , 0.3835 , 0.4143 ,
0.6828 , 0.4388 , 0.7579 , 0.3558 ,
0.9001 , 0.6123 , 0.4701 , 0.2255 ,
0.6797 , 0.8035 , 0.5837 , 0.5936 ,
0.6256 , 0.7106 , 0.662 , 0.4649 ,
0.6674 , 0.7371 , 0.6386 , 0.584 ,
0.8121 , 0.7681 , 0.6276 , 0.4326 ,
0.6753 , 0.62 , 0.5349 , 0.3694 ,
0.8184 , 0.6875 , 0.4171 , 0.599 ,
0.5361 , 0.6362 , 0.4277 , 0.4703 ,
0.6011 , 0.6919 , 0.7274 , 0.4548 ,
0.4886 , 0.4174 , 0.3246 , 0.3723 ,
0.7504 , 0.6154 , 0.5458 , 0.4552 ,
0.5781 , 0.5544 , 0.6497 , 0.4266 ,
0.7847 , 0.6114 , 0.6467 , 0.4577 ,
0.5891 , 0.4394 , 0.3231 , 0.5606 ,
0.7605 , 0.6754 , 0.5468 , 0.5673 ,
0.7693 , 0.6373 , 0.7643 , 0.5382 ,