vars<-c("median","l95","u95") k=8 for (i in seq_along(vars)){ all_imfs<-iceemdanP(eval(as.name(paste0("tmp_",vars[i]))),ensemble_size=10000)#[,1:k] x<-ts.union(all_imfs,eval(as.name(paste0("tmp_",vars[i])))-rowSums(all_imfs)) colnames(x)<-c(paste0("IMF",1:k),"Residual") assign(paste0("final_imfs_",vars[i]),x,envir = .GlobalEnv) }