Generated data copy for RESALI analysis

main
Corentin Choisy 8 months ago
parent 5cb862072c
commit 1efe30e6e3

@ -1,7 +1,3 @@
}
## create design matrix for covariate part
if(m>=1){
designX <- -get_designX(X, DSF, m, I, q, n)
## create penalization matrix ## create penalization matrix
acoefs <- get_acoefs(RSM, DSF, m, I, q, n_sigma) acoefs <- get_acoefs(RSM, DSF, m, I, q, n_sigma)
## update number of parameters to be optimized ## update number of parameters to be optimized
@ -510,3 +506,7 @@ GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",contr
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",control = ctrl_GPCMlasso(lambda = 10000000,adaptive=F),DSF = F,cv=F) GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",control = ctrl_GPCMlasso(lambda = 10000000,adaptive=F),DSF = F,cv=F)
GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GRSM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F) GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GRSM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)
tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT) tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
wwwwww <- read.csv('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/3A_200.csv')
table(wwwwww$dif.detect.1)
table(wwwwww$dif.detect.1)/400
sum(table(wwwwww$dif.detect.1)/400)

@ -0,0 +1,84 @@
## Liste des scenarios
results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
results2 <- sort(results2)
results <- c(results,results2)
## Importer l'analyse resali pour chaque scenario
for (r in results[21:length(results)]) {
cat('--------------------------------------------------------------------------\n')
cat(paste0(r,"\n"))
cat('--------------------------------------------------------------------------\n')
#### Importer les datas
scen <- as.numeric(gsub("[A,B,C,D,E,F,G,_]","",substr(r,0,3)))
if (substr(r,start=nchar(r)-1,stop=nchar(r))=="50") {
N <- 50
}
if (substr(r,start=nchar(r)-2,stop=nchar(r))=="100") {
N <- 100
}
if (substr(r,start=nchar(r)-2,stop=nchar(r))=="200") {
N <- 200
}
if (substr(r,start=nchar(r)-2,stop=nchar(r))=="300") {
N <- 300
}
if (scen<5) {
datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N',N,'/scenario_',r,'.csv'))
}
if (scen>=5) {
datt <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',N,'/scenario_',r,'.csv'))
}
#### Importer l'analyse
analyse <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection/',r,".csv"))
#### Pour chaque replication
for (k in 1:1000) {
if (k%%100==0) {
cat(paste0("N = ",k," / 1000\n"))
}
datt[datt$replication==k,"dif.detect.1"] <- analyse[analyse$X==k,"dif.detect.1"]
datt[datt$replication==k,"dif.detect.2"] <- analyse[analyse$X==k,"dif.detect.2"]
datt[datt$replication==k,"dif.detect.3"] <- analyse[analyse$X==k,"dif.detect.3"]
datt[datt$replication==k,"dif.detect.4"] <- analyse[analyse$X==k,"dif.detect.4"]
datt[datt$replication==k,"dif.detect.unif.1"] <- analyse[analyse$X==k,"dif.detect.unif.1"]
datt[datt$replication==k,"dif.detect.unif.2"] <- analyse[analyse$X==k,"dif.detect.unif.2"]
datt[datt$replication==k,"dif.detect.unif.3"] <- analyse[analyse$X==k,"dif.detect.unif.3"]
datt[datt$replication==k,"dif.detect.unif.4"] <- analyse[analyse$X==k,"dif.detect.unif.4"]
if (scen==3 | scen==4 | scen>=13) {
datt[datt$replication==k,"dif.detect.5"] <- analyse[analyse$X==k,"dif.detect.5"]
datt[datt$replication==k,"dif.detect.6"] <- analyse[analyse$X==k,"dif.detect.6"]
datt[datt$replication==k,"dif.detect.7"] <- analyse[analyse$X==k,"dif.detect.7"]
datt[datt$replication==k,"dif.detect.unif.5"] <- analyse[analyse$X==k,"dif.detect.unif.5"]
datt[datt$replication==k,"dif.detect.unif.6"] <- analyse[analyse$X==k,"dif.detect.unif.6"]
datt[datt$replication==k,"dif.detect.unif.7"] <- analyse[analyse$X==k,"dif.detect.unif.7"]
}
}
datt[is.na(datt$dif.detect.1),"dif.detect.1"] <- ""
datt[is.na(datt$dif.detect.2),"dif.detect.2"] <- ""
datt[is.na(datt$dif.detect.3),"dif.detect.3"] <- ""
datt[is.na(datt$dif.detect.4),"dif.detect.4"] <- ""
datt[is.na(datt$dif.detect.unif.1),"dif.detect.unif.1"] <- ""
datt[is.na(datt$dif.detect.unif.2),"dif.detect.unif.2"] <- ""
datt[is.na(datt$dif.detect.unif.3),"dif.detect.unif.3"] <- ""
datt[is.na(datt$dif.detect.unif.4),"dif.detect.unif.4"] <- ""
if (scen==3 | scen==4 | scen>=13) {
datt[is.na(datt$dif.detect.5),"dif.detect.5"] <- ""
datt[is.na(datt$dif.detect.6),"dif.detect.6"] <- ""
datt[is.na(datt$dif.detect.7),"dif.detect.7"] <- ""
datt[is.na(datt$dif.detect.unif.5),"dif.detect.unif.5"] <- ""
datt[is.na(datt$dif.detect.unif.6),"dif.detect.unif.6"] <- ""
datt[is.na(datt$dif.detect.unif.7),"dif.detect.unif.7"] <- ""
}
write.csv(datt,paste0("/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data/",r,".csv"))
}
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