#Now get

tb_v_gam_CAI

tb_v_gam_fus

tb_v_kriging_CAI

tb_v_kriging_fus

methods_names <- c("tb_v_gam_CAI","tb_v_gam_fus","tb_v_kriging_CAI","tb_v_kriging_fus")

list_prop_obj <- vector("list",length=length(methods_names))

for(i in 1:length(methods_names)){

  tb <- list_tb[[methods_names[i]]]

  names_id <- c("pred_mod","prop_month")

  names_mod <-unique(tb$pred_mod)

  list_prop_obj[[i]] <- calc_stat_prop_tb_diagnostic(names_mod,names_id,tb)

  names(list_prop_obj)[i] <- methods_names[i]

  #avg_tb <- prop_obj$avg_tb

}

ac_prop_tb_list <- extract_list_from_list_obj(list_prop_obj,"avg_tb")

nb_rows <- sapply(ac_prop_tb_list,FUN=nrow)

method_interp_names<-c("gam_CAI","gam_fus","kriging_CAI","kriging_fus")

for(i in 1:length(methods_names)){

  avg_tb<-ac_prop_tb_list[[i]]

  avg_tb$method_interp <-rep(x=method_interp_names[i],times=nb_rows[i])

  ac_prop_tb_list[[i]] <- avg_tb  

}

#lapply(methods_names,function(i) {rep(x[i],nrows[i],times[i])},times=nb_rows)

#names(ac_prop_tb_list) <- names(list_prop_obj)

t44 <- do.call(rbind,ac_prop_tb_list)

View(t44)

t44[which.min(t44$rmse),]

test <- t44[order(t44$rmse),]

test2<-test[test$method_interp%in% c("gam_fus","gam_CAI"),]

test2[1:24,]

#head(ac_prop_tb)

#list_prop_obj$avg_tb

#xyplot(as.formula(plot_formula),group=pred_mod,type="b",

#       data=avg_tb,

#       main=paste("rmse ",plot_name,sep=" "),

#       pch=1:length(avg_tb$pred_mod),

#       par.settings=list(superpose.symbol = list(

#         pch=1:length(avg_tb$pred_mod))),

#       auto.key=list(columns=5))