diff --git a/R/for_BBS/BBS_ta_nbin3.R b/R/for_BBS/BBS_ta_nbin3.R
deleted file mode 100644
index ed72596..0000000
--- a/R/for_BBS/BBS_ta_nbin3.R
+++ /dev/null
@@ -1,35 +0,0 @@
-# This is the tail analysis with 75% threshold 
-# so we chose only for communities which are longer than 45 years
-
-yr_threshold<-41 # mean of nyr across all communities used for BioDyn study
-resloc<-"../../Results/for_BBS/"
-uroutes<-readRDS("../../DATA/for_BBS/wrangled_data/unique_routes_all.RDS")
-uroutes<-data.frame(Country_State_Route=uroutes)
-
-#------------ Now compute and plot the tail stats ---------------------
-siteid_nbin3<-c()
-for(i in 1:nrow(uroutes)){
-  siteid<-uroutes$Country_State_Route[i]
-  resloc_input<-paste("../../DATA/for_BBS/wrangled_data/",siteid,"/",sep="")
-  df<-readRDS(paste(resloc_input,"input_mat_for_tailanal.RDS",sep="")) # dataframe with species timeseries along column
-  nyrused<-nrow(df)
-  
-  if(nyrused<yr_threshold){
-    cat("communities with less than ", yr_threshold, " years of data, i = ", i," \n")
-  }else{
-    siteid_nbin3<-c(siteid_nbin3,siteid)
-    resloc_output<-paste(resloc,siteid,"/","nbin3/",sep="")
-    if(!dir.exists(resloc_output)){
-      dir.create(resloc_output)
-    }
-    #----------- analysis with covary sp ----------------
-    res<-tail_analysis(mat = df, resloc = resloc_output, nbin = 3)
-    cat("---------- i= ",i," routeid=",siteid," ----------\n")
-  }
-}
-
-
-
-
-
-